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Methods For Improving The Reconstruction Of Diffuse Optical Tomography For Breast Cancer Detection
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Book Synopsis Methods for Improving the Reconstruction of Diffuse Optical Tomography for Breast Cancer Detection by : Murad Mohsen Althobaiti
Download or read book Methods for Improving the Reconstruction of Diffuse Optical Tomography for Breast Cancer Detection written by Murad Mohsen Althobaiti and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Deep Learning Methods for Reconstruction and Analysis of Diffuse Optical Tomography Images of Breast Cancer Lesions by : Hanene Ben Yedder
Download or read book Deep Learning Methods for Reconstruction and Analysis of Diffuse Optical Tomography Images of Breast Cancer Lesions written by Hanene Ben Yedder and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of an accurate, efficient, portable, and affordable method for identifying breast cancer is critical for both early detection and improved prognosis. Medical imaging modalities play a critical role in cancer screening and treatment monitoring. Diffuse optical tomography (DOT) is a non-invasive imaging modality that can be used in a low-complexity probe design, resulting in an inexpensive portable imaging diagnostic device with low power consumption. In recent years, machine learning techniques have created transformative opportunities for medical image reconstruction and analysis, helping move toward data-driven algorithm designs wherein computational power is augmented with physics priors to push the accuracy and fairness of image driven diagnosis to new limits. In this thesis, we present multiple deep learning-based medical image reconstruction and analysis approaches for screening breast cancer lesions acquired by DOT. First, an end-to-end image reconstruction model from sensor-domain data is proposed, where physics-based simulation is leveraged to address the lack of available real-world data required for training. Next, we adopt a transfer learning strategy to align and translate the sensor domain distribution between in silico and real-world data and propose a novel loss to promote appearance similarity and penalize artifacts. Following up on this we propose a joint reconstruction and localization solution that simultaneously attends to the most important features while ensuring better lesion localization. Finally, we propose an orthogonal multi-frequency fusion solution for direct prediction of the end task from sensor signal data, increasing diagnosis accuracy at a reduced computational cost. Extending a portable device with such diagnosis ability promises to improve first-line treatment throughput. These contributions demonstrate the promising role of deep learning in DOT image reconstruction and diagnosis. Combined, our contributions open the path towards personalized medicine for non-invasive portable diagnosis and treatment monitoring of breast cancer in the very near future.
Book Synopsis Diffuse Optical Tomography by : Huabei Jiang
Download or read book Diffuse Optical Tomography written by Huabei Jiang and published by CRC Press. This book was released on 2018-09-03 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by an authority involved in the field since its nascent stages, Diffuse Optical Tomography: Principles and Applications is a long-awaited profile of a revolutionary imaging method. Diffuse Optical Tomography (DOT) provides spatial distributions of intrinsic tissue optical properties or molecular contrast agents through model-based reconstruction algorithms using NIR measurements along or near the boundary of tissue. Despite the practical value of DOT, many engineers from electrical or applied mathematics backgrounds do not have a sufficient understanding of its vast clinical applications and portability value, or its uncommon advantages as a tool for obtaining functional, cellular, and molecular parameters. A collection of the author’s research and experience, this book fuses historical perspective and experiential anecdotes with fundamental principles and vital technical information needed to successfully apply this technology—particularly in medical imaging. This reference finally outlines how to use DOT to create experimental image systems and adapt the results of laboratory studies for use in clinical applications including: Early-stage detection of breast tumors and prostate cancer "Real-time" functional brain imaging Joint imaging to treat progressive diseases such as arthritis Monitoring of tumor response New contrast mechanisms and multimodality methods This book covers almost every aspect of DOT—including reconstruction algorithms based on nonlinear iterative Newton methods, instrumentation and calibration methods in both continuous-wave and frequency domains, and important issues of imaging contrast and spatial resolution. It also addresses phantom experiments and the development of various image-enhancing schemes, and it describes reconstruction methods based on contrast agents and fluorescence DOT. Offering a concise description of the particular problems involved in optical tomography, this reference illustrates DOT’s fundamental foundations and the principle of image reconstruction. It thoroughly explores computational methods, forward mathematical models, and inverse strategies, clearly illustrating solutions to key equations.
Book Synopsis Ultrasound Guided Diffuse Optical Tomography for Breast Cancer Diagnosis by : K. M. Shihab Uddin
Download or read book Ultrasound Guided Diffuse Optical Tomography for Breast Cancer Diagnosis written by K. M. Shihab Uddin and published by . This book was released on 2020 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: According to National Breast Cancer Society, one in every eight women in United States is diagnosed with breast cancer in her lifetime. American Cancer Society recommends a semi-annual breast-cancer screening for every woman which can be heavily facilitated by the availability of low-cost, non-invasive diagnostic method with good sensitivity and penetration depth. Ultrasound (US) guided Diffuse Optical Tomography (US-guided DOT) has been explored as a breast-cancer diagnostic and screening tool over the past two decades. It has demonstrated a great potential for breast-cancer diagnosis, treatment monitoring and chemotherapy-response prediction. In this imaging method, optical measurements of four different wavelengths are used to reconstruct unknown optical absorption maps which are then used to calculate the hemoglobin concentration of the US-visible lesion. This dissertation focuses on algorithm development for robust data processing, imaging reconstruction and optimal breast cancer diagnostic strategy development in DOT. The inverse problem in DOT is ill-posed, ill-conditioned, and underdetermined. This makes the task of image reconstruction challenging, and thus regularization-based method need to be employed. In this dissertation, a simple two-step reconstruction method that can produce accurate image estimates in DOT is proposed and investigated. In the first step, a truncated Moore-Penrose Pseudoinverse solution is computed to obtain a preliminary estimate of the image. This estimate can be reliably determined from the measured data; subsequently, this preliminary estimate is incorporated into the design of a penalized least squares estimator that is employed to compute the final image estimate. Using physical phantoms, the proposed method was demonstrated to yield more accurate reconstruction compared to other conventional reconstruction methods. The method was also evaluated with clinical data that included 10 benign and 10 malignant cases. The capability of reconstructing high contrast malignant lesions improved by the use of the proposed method.Reconstructed absorption maps are prone to image artifacts from outliers in measurement data from tissue heterogeneity, bad coupling between tissue and light guides, and motion by patient or operator. In this dissertation, a new automated iterative perturbation correction algorithm is proposed to reduce image artifacts based on the structural similarity index (SSIM)) of absorption maps of four optical wavelengths. The SSIM was calculated for each wavelength to assess its similarity with other wavelengths. Absorption map was iteratively reconstructed and projected back into measurement space to quantify projection error. Outlier measurements with highest projection errors were iteratively removed until all wavelength images were structurally similar with SSIM values greater than a threshold. Clinical data demonstrated statistically significant improvement in image artifact reduction.US guidance with DOT helps to reduce false positive rate and hence reduce number of unnecessary biopsies. However, DOT data processing and image reconstruction speed remains slow compared to real-time US. Real-time or near real time diagnosis with DOT is an important step toward the clinical translation of the US-guided DOT. In this dissertation, to address this important need, we present a two-stage diagnostic strategy that is computationally efficient and accurate. In the first stage, benign lesions are identified in near real-time by use of a random forest classifier acting on the DOT measurements and radiologists' US diagnostic scores. The lesions that cannot be reliably classified by the random forest classifier will be passed on to the image reconstruction stage. Functional information from the reconstructed hemoglobin concentrations is used by a Support Vector Machine (SVM) classifier for diagnosis in the second stage. This two-step classification approach that combines both perturbation data and functional features results in improved classification, as quantified using the receiver operating characteristic (ROC) curve. Using this two-step approach, area under the ROC curve (AUC) is 0.937 ± 0.009 with sensitivity of 91.4% and specificity of 85.7%. While using functional features and US score, AUC is 0.892 ± 0.027 with sensitivity of 90.2% and specificity of 74.5%. The specificity increased by more than 10% due to the implementation of the random forest classifier.
Book Synopsis A Diffuse Optical Tomography System Combined with X-ray Mammography for Improved Breast Cancer Detection by : Thomas John Brukilacchio
Download or read book A Diffuse Optical Tomography System Combined with X-ray Mammography for Improved Breast Cancer Detection written by Thomas John Brukilacchio and published by . This book was released on 2003 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: The central thesis of this dissertation states that optical imaging of diffuse tissues must be combined in co-registration with a recognized gold standard of mammographic screening, i.e. X-ray mammography, to gain wide acceptance in the clinical environment. This multi-modality imaging approach promises to overcome the deficiencies of both imaging modalities by drawing on the strengths of each. Functional and structural image contrast would be provided by optical and high-resolution structural contrast by X-ray. Furthermore, the structural information provided by X-ray could be used to improve the optical image reconstruction by providing boundary information and soft constraints for weakly correlated structural contrast. Ultimately, image-processing techniques could be developed to provide the radiologist with a three-dimensional image indicative of both optical and X-ray contrast that would provide much greater information content than either modality alone.
Book Synopsis Ultrasound-guided Optical Techniques for Cancer Diagnosis by : Atahar Kamal Mostafa
Download or read book Ultrasound-guided Optical Techniques for Cancer Diagnosis written by Atahar Kamal Mostafa and published by . This book was released on 2019 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: Worldwide, breast cancer is the most common cancer among women. In the United States alone, the American cancer society has estimated there will be 271,270 new breast cancer cases in 2019, and 42,260 lives will be lost to the disease. Ultrasound (US), mammography, and magnetic resonance imaging (MRI) are regularly used for breast cancer diagnosis and therapy monitoring. However, they sometimes fail to diagnose breast cancer effectively. These shortcomings have motivated researchers to explore new modalities. One of these modalities, diffuse optical tomography (DOT), utilizes near-infrared (NIR) light to reveal the optical properties of tissue. NIR-based DOT images the contrast between a suspected lesion's location and the background tissue, caused by the higher NIR absorption of the hemoglobin which characterizes tumors. The limitation of high light scattering inside tissue is minimized by using ultrasound image to find the tumor location.This thesis focuses on developing a compact, low-cost ultrasound guided diffuse optical tomography imaging system and on improving optical image reconstruction by extracting the tumor's location and size from co-registered ultrasound images. Several electronic components have been redesigned and optimized to save space and cost and to improve the user experience. In terms of software and algorithm development, manual extraction of tumor information from ultrasound images has been replaced by using a semi-automated ultrasound image segmentation algorithm that reduces the optical image reconstruction time and operator dependency. This system and algorithm have been validated with phantom and clinical data and have demonstrated their efficacy. An ongoing clinical trial will continue to gather more patient data to improve the robustness of the imaging algorithm.Another part of this research focuses on ovarian cancer diagnosis. Ovarian cancer is the most deadly of all gynecological cancers, with a less than 50% five-year survival rate. This cancer can evolve without any noticeable symptom, which makes it difficult to diagnose in an early stage. Although ultrasound-guided photoacoustic tomography (PAT) has demonstrated potential for early detection of ovarian cancer, clinical studies have been very limited due to the lack of robust PAT systems.In this research, we have customized a commercial ultrasound system to obtain real-time co-registered PAT and US images. This system was validated with several phantom studies before use in a clinical trial. PAT and US raw data from 30 ovarian cancer patients was used to extract spectral and statistical features for training and testing classifiers for automatic diagnosis. For some challenging cases, the region of interest selection was improved by reconstructing co-registered Doppler images. This study will be continued in order to obtain quantitative tissue properties using US-guided PAT.
Book Synopsis Optical Imaging of Breast Cancers by : Yan Xu
Download or read book Optical Imaging of Breast Cancers written by Yan Xu and published by . This book was released on 2013 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Elastic-optical Tomography for Breast Cancer Imaging by : Hua Liu
Download or read book Elastic-optical Tomography for Breast Cancer Imaging written by Hua Liu and published by . This book was released on 2010 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation is devoted to studies of elastic-optical tomography for breast cancer imaging. Efforts are made to exploration of development and application of numerical optimization methods to the inverse problem which have a great stability and accuracy on the reconstructed images. Elastic-optical tomography model has been created and evaluated to account for the compression-induced changes in optical tomography. The major accomplishments in the study are summarized in the following. First, an improved Levenberg-Marquardt method is developed for diffuse optical tomography problems to take into account the magnitude variation and reasonable range of the optical coefficients. A scaling matrix scheme is introduced to reduce the effect of poor scaling by using an ellipsoidal trust region instead of a spherical trust region. A lower bound is imposed to avoid non-positive results. The proposed approach is capable of detecting inclusions in different shapes with high object to background optical contrast even under the impact of noise. We also applied quasi-Newton methods (BFGS and lm-BFGS methods) to solve the inverse problems in the diffuse optical tomography. A more efficient inexact line search strategy is employed in the method. For large-scale problems, lm-BFGS can help reduce the memory requirement. Good reconstruction can be achieved in terms of inclusion location and size in both numerical and experimental studies. A hybrid method is then proposed by combining the improved Levenberg-Marquardt method and quasi-Newton method. The hybrid method can switch between the above mentioned two methods based on the iteration results to avoid slow convergence. Studies show that the hybrid method can improve the quality of the reconstructed optical images compared to Levenberg-Marquardt method and quasi-Newton method. A very important portion in this dissertation is the development of elastic-optical tomography to predict how optical properties change according to the externally applied compression for breast cancer imaging. Both the mechanical and optical properties of the breast tissue are incorporated into the model. Results show that the proposed model can be used to interpret the possible misleading information caused by compression induced changes in optical images and recover the actual optical contrast, location and size of the malignant tumors.
Book Synopsis Diffuse Optical Tomography by : Ruixin Jiang
Download or read book Diffuse Optical Tomography written by Ruixin Jiang and published by . This book was released on 2012 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diffuse Optical Tomography has drawn more and more interests in the biomedical field over the recent couple of decades due to its ability to noninvasively recover not only tissue structural information but also functional and molecular properties. The contrasts that optical parameters could demonstrate in DOT are usually higher than those of the conventional methods. Based on these contrasts, different approaches had been developed applying DOT for imaging, and so far lots of efforts were spent on detecting breast cancer by imaging tissue absorption and scattering coefficients as well as hemoglobin concentration and oxygen saturation level. In this work, we tried to expand the ability of DOT in breast cancer detection by introducing Phase-contrast diffuse optical tomography (PCDOT). PCDOT uses near-infrared diffusing light to non-invasively reconstruct tissue refractive index (RI) distribution. RI depends on the tissue's physical and chemical properties and previous study revealed that it might serve as a promising imaging parameter in breast cancer detection. We've first developed a 2-step method to improve the PCDOT image both qualitatively and quantitatively at single-wavelength; then we've introduced a multispectral PCDOT algorithm to more efficiently reconstruct RI simultaneously with other tissue functional parameters and attempted to improve this algorithm by different structural regularization methods.
Book Synopsis Three Dimensional Near-infrared Optical Imaging Using Ultrasound Guidance for Breast Cancer Detection and Diagnosis by : Minming Huang
Download or read book Three Dimensional Near-infrared Optical Imaging Using Ultrasound Guidance for Breast Cancer Detection and Diagnosis written by Minming Huang and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation focuses on the study of three-dimensional near-infrared (NIR) imaging reconstruction using ultrasound localization for breast cancer detection and diagnosis. With the 3D NIR forward model for reflection geometry built and investigated, successful reconstruction of both absorption and scattering coefficients has been obtained and evaluated using both a phantom study and initial clinic data. In this work, we first introduce a dual mesh optical reconstruction method with depth correction using a priori ultrasound information. It can significantly improve the reconstructed absorption distributions in deeper target layers. Clinical results have shown improved correlation between reconstructed total hemoglobin concentrations and the histological micorvessel density counts. Next, a combined Tikhonov regularization and dual mesh scheme based on finite element method (FEM) is proposed to solve the inter-parameter cross talk between the scattering coefficient and absorption coefficient. In this approach, the optimal regularization factor is given by the standard L-curve. Different regularization factors have been assigned to the target region and non-target region to incorporate the priori target information from the co-registered ultrasound images. Both phantom experiments and clinic examples have shown that this new approach has the ability to reconstruct the absorption and diffusion coefficients simultaneously, and the reconstructed target absorption and diffusion maps have no depth dependence effect. Finally, a simple two-layer model is generated and studied to solve a clinical issue related to the chest wall, which is a mixture of bones and muscles. For small breasts, the chest wall appears within 2–3 cm distance from the skin surface. As a result, the simple one layer model is not accurate. Furthermore, for some cases, there is also an obvious chest wall mismatch between the reference site and lesion site. To solve this clinical issue, a simplified two-layer model is generated and a fitting method is adopted to estimate the optical properties of both layers. Then a correction method is applied to correct for the chest wall mismatch between the lesion site and reference site. With this scheme, phantom targets located on top of the chest wall phantom layer can be reconstructed with good contrast and resolution.
Book Synopsis Diffuse Optical Tomography System in Soft Tissue Tumor Detection by : Umamaheswari Kumarasamy
Download or read book Diffuse Optical Tomography System in Soft Tissue Tumor Detection written by Umamaheswari Kumarasamy and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Topical review of recent trends in Modeling and Regularization methods of Diffuse Optical Tomography (DOT) system promotes the optimization of the forward and inverse modeling methods which provides a 3D cauterization at a faster rate of 40frames/second with the help of a laser torch as a hand-held device. Analytical, Numerical and Statistical methods are reviewed for forward and inverse models in an optical imaging modality. The advancement in computational methods is discussed for forward and inverse models along with Optimization techniques using Artificial Neural Networks (ANN), Genetic Algorithm (GA) and Artificial Neuro Fuzzy Inference System (ANFIS). The studies carried on optimization techniques offers better spatial resolution which improves quality and quantity of optical images used for morphological tissues comparable to breast and brain in Near Infrared (NIR) light. Forward problem is based on the location of sources and detectors solved statistically by Monte Carlo simulations. Inverse problem or closeness in optical image reconstruction is moderated by different regularization techniques to improve the spatial and temporal resolution. Compared to conventional methods the ANFIS structure of optimization for forward and inverse modeling provides early detection of Malignant and Benign tumor thus saves the patient from the mortality of the disease. The ANFIS technique integrated with hardware provides the dynamic 3D image acquisition with the help of NIR light at a rapid rate. Thereby the DOT system is used to continuously monitor the Oxy and Deoxyhemoglobin changes on the tissue oncology.
Book Synopsis Mechanical and Optical Methods for Breast Cancer Imaging by :
Download or read book Mechanical and Optical Methods for Breast Cancer Imaging written by and published by . This book was released on 2010 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Third, encouraged by the success of linear elasto-mammography and nonlinear elastography, a nonlinear elasto-mammography method is proposed. Mammography projections are taken before and after breast compression and displacement information is extracted for reconstruction of nonlinear breast tissue properties. Numerical phantom study is conducted and results show the proposed nonlinear elasto-mammography is potential to identify and characterize breast tumors in clinic. Finally, we switch from mechanical to optical method for breast cancer imaging. We develop a finite-element-based algorithm to solve the inverse problem of frequent-domain diffusion equation. With the analytical form of gradients, the adjoint method is expanded to complex domain for the reconstruction of optical parameters in diffuse optical tomography. Specific numerical simulation is carried out and compared with phantom experiment. The results show that the adjoint-based algorithm is efficient and robust for reconstructing the optical parameters.
Book Synopsis A Multimodal Breast Cancer Imaging System Using Coregistered Dynamic Diffuse Optical Tomography and Digital Breast Tomosynthesis by : Bernhard B. Zimmermann
Download or read book A Multimodal Breast Cancer Imaging System Using Coregistered Dynamic Diffuse Optical Tomography and Digital Breast Tomosynthesis written by Bernhard B. Zimmermann and published by . This book was released on 2017 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diffuse optical tomography (DOT) is an emerging noninvasive functional imaging method for breast cancer diagnosis and neoadjuvant chemotherapy monitoring. In particular, the multimodal approach of combining DOT with x-ray digital breast tomosynthesis (DBT) is especially synergistic as DBT prior information can be used to enhance the DOT reconstruction. DOT, in turn, provides a functional information overlay onto the mammographic images, increasing sensitivity and specificity to cancer pathology. We describe a dynamic DOT apparatus designed for tight integration with commercial DBT scanners and providing a fast (1 Hz+) image acquisition rate to enable tracking of hemodynamic changes induced by the mammographic breast compression. The most significant advance enabling fast acquisition was the design and construction of a direct analog-to-digital conversion frequency-domain near-infrared spectroscopy (FD-NIRS) component. It achieves simultaneous dual wavelength operation at 685 nm and 830 nm by concurrent 67.5 MHz and 75 MHz frequency modulation of each laser source, respectively, followed by digitization using a high-speed analog to digital converter and real-time hybrid FPGA-assisted demodulation by discrete Fourier transform (DFT). The overall DOT system integrates 96 CW-NIRS and 24 FD-NIRS source locations, as well as 32 CW-NIRS and 20 FD-NIRS detection locations into low-profile plates that mate to the DBT compression paddle and x-ray detector cover, respectively. The plates and the embedded optical fibers are made of plastic to minimize x-ray absorption and thus allow true simultaneous acquisition of the DBT image. We first characterize each major system component individually, and then demonstrate overall performance using static and dynamic tissue-like phantoms, as well as in vivo images acquired from the pool of patients recalled for breast biopsies at the Massachusetts General Hospital Breast Imaging Division.
Book Synopsis New Horizons in Time-Domain Diffuse Optical Spectroscopy and Imaging by : Yoko Hoshi
Download or read book New Horizons in Time-Domain Diffuse Optical Spectroscopy and Imaging written by Yoko Hoshi and published by MDPI. This book was released on 2020-06-23 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Jöbsis was the first to describe the in vivo application of near-infrared spectroscopy (NIRS), also called diffuse optical spectroscopy (DOS). NIRS was originally designed for the clinical monitoring of tissue oxygenation, and today it has also become a useful tool for neuroimaging studies (functional near-infrared spectroscopy, fNIRS). However, difficulties in the selective and quantitative measurements of tissue hemoglobin (Hb), which have been central in the NIRS field for over 40 years, remain to be solved. To overcome these problems, time-domain (TD) and frequency-domain (FD) measurements have been tried. Presently, a wide range of NIRS instruments are available, including commonly available commercial instruments for continuous wave (CW) measurements, based on the modified Beer–Lambert law (steady-state domain measurements). Among these measurements, the TD measurement is the most promising approach, although compared with CW and FD measurements, TD measurements are less common, due to the need for large and expensive instruments with poor temporal resolution and limited dynamic range. However, thanks to technological developments, TD measurements are increasingly being used in research, and also in various clinical settings. This Special Issue highlights issues at the cutting edge of TD DOS and diffuse optical tomography (DOT). It covers all aspects related to TD measurements, including advances in hardware, methodology, the theory of light propagation, and clinical applications.
Book Synopsis Tomographic Image Reconstruction by : Shiya Xu
Download or read book Tomographic Image Reconstruction written by Shiya Xu and published by . This book was released on 2014 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conventional 2D mammography was the most effective approach to detecting early stage breast cancer in the past decades of years. Tomosynthetic breast imaging is a potentially more valuable 3D technique for breast cancer detection. The limitations of current tomosynthesis systems include a longer scanning time than a conventional digital X-ray modality and a low spatial resolution due to the movement of the single X-ray source. Dr.Otto Zhou's group proposed the concept of stationary digital breast tomosynthesis (s-DBT) using a Carbon Nano-Tube (CNT) based X-ray source array. Instead of mechanically moving a single X-ray tube, s-DBT applies a stationary X-ray source array, which generates X-ray beams from different view angles by electronically activating the individual source prepositioned at the corresponding view angle, therefore eliminating the focal spot motion blurring from sources. The scanning speed is determined only by the detector readout time and the number of sources regardless of the angular coverage spans, such that the blur from patient's motion can be reduced due to the quick scan. S-DBT is potentially a promising modality to improve the early breast cancer detection by providing decent image quality with fast scan and low radiation dose. DBT system acquires a limited number of noisy 2D projections over a limited angular range and then mathematically reconstructs a 3D breast. 3D reconstruction is faced with the challenges of cone-beam and flat-panel geometry, highly incomplete sampling and huge reconstructed volume. In this research, we investigated several representative reconstruction methods such as Filtered backprojection method (FBP), Simultaneous algebraic reconstruction technique (SART) and Maximum likelihood (ML). We also compared our proposed statistical iterative reconstruction (IR) with particular prior and computational technique to these representative methods. Of all available reconstruction methods in this research, our proposed statistical IR appears particularly promising since it provides the flexibility of accurate physical noise modeling and geometric system description. In the following chapters, we present multiple key techniques of statistical IR to tomosynthesis imaging data to demonstrate significant image quality improvement over conventional techniques. These techniques include the physical modeling with a local voxel-pair based prior with the flexibility in its parameters to fine-tune image quality, the pre-computed parameter κ incorporated with the prior to remove the data dependence and to achieve a predictable resolution property, an effective ray-driven technique to compute the forward and backprojection and an over-sampled ray-driven method to perform high resolution reconstruction with a practical region of interest (ROI) technique. In addition, to solve the estimation problem with a fast computation, we also present a semi-quantitative method to optimize the relaxation parameter in a relaxed order-subsets framework and an optimization transfer based algorithm framework which potentially allows less iterations to achieve an acceptable convergence. The phantom data is acquired with the s-DBT prototype system to assess the performance of these particular techniques and compare our proposed method to those representatives. The value of IR is demonstrated in improving the detectability of low contrast and tiny micro-calcification, in reducing cross plane artifacts, in improving resolution and lowering noise in reconstructed images. In particular, noise power spectrum analysis (NPS) indicates a superior noise spectral property of our proposed statistical IR, especially in the high frequency range. With the decent noise property, statistical IR also provides a remarkable reconstruction MTF in general and in different areas within a focus plane. Although computational load remains a significant challenge for practical development, combined with the advancing computational techniques such as graphic computing, the superior image quality provided by statistical IR will be realized to benefit the diagnostics in real clinical applications.
Book Synopsis Time Reversal Optical Tomography and Decomposition Methods for Detection and Localization of Targets in Highly Scattering Turbid Media by : Binlin Wu
Download or read book Time Reversal Optical Tomography and Decomposition Methods for Detection and Localization of Targets in Highly Scattering Turbid Media written by Binlin Wu and published by . This book was released on 2013 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: New near-infrared (NIR) diffuse optical tomography (DOT) approaches were developed to detect, locate, and image small targets embedded in highly scattering turbid media. The first approach, referred to as time reversal optical tomography (TROT), is based on time reversal (TR) imaging and multiple signal classification (MUSIC). The second approach uses decomposition methods of non-negative matrix factorization (NMF) and principal component analysis (PCA) commonly used in blind source separation (BSS) problems, and compare the outcomes with that of optical imaging using independent component analysis (OPTICA). The goal is to develop a safe, affordable, noninvasive imaging modality for detection and characterization of breast tumors in early growth stages when those are more amenable to treatment. The efficacy of the approaches was tested using simulated data, and experiments involving model media and absorptive, scattering, and fluorescent targets, as well as, "realistic human breast model" composed of ex vivo breast tissues with embedded tumors. The experimental arrangements realized continuous wave (CW) multi-source probing of samples and multi-detector acquisition of diffusely transmitted signal in rectangular slab geometry. A data matrix was generated using the perturbation in the transmitted light intensity distribution due to the presence of absorptive or scattering targets. For fluorescent targets the data matrix was generated using the diffusely transmitted fluorescence signal distribution from the targets. The data matrix was analyzed using different approaches to detect and characterize the targets. The salient features of the approaches include ability to: (a) detect small targets; (b) provide three-dimensional location of the targets with high accuracy (~within a millimeter or 2); and (c) assess optical strength of the targets. The approaches are less computation intensive and consequently are faster than other inverse image reconstruction methods that attempt to reconstruct the optical properties of every voxel of the sample volume. The location of a target was estimated to be the weighted center of the optical property of the target. Consequently, the locations of small targets were better specified than those of the extended targets. It was more difficult to retrieve the size and shape of a target. The fluorescent measurements seemed to provide better accuracy than the transillumination measurements. In the case of ex vivo detection of tumors embedded in human breast tissue, measurements using multiple wavelengths provided more robust results, and helped suppress artifacts (false positives) than that from single wavelength measurements. The ability to detect and locate small targets, speedier reconstruction, combined with fluorophore-specific multi-wavelength probing has the potential to make these approaches suitable for breast cancer detection and diagnosis.
Book Synopsis Time Domain Image Reconstruction Methods for Transmission Ultrasound Computed Tomography by : Mailyn Pérez Liva
Download or read book Time Domain Image Reconstruction Methods for Transmission Ultrasound Computed Tomography written by Mailyn Pérez Liva and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast cancer (BC) is the leading cause of cancer-related death for women in Europe, and the second one after lung cancer in the US [World Cancer Report, 2008]. Early detection is very important for the survival rate of BC, because the smaller the local extension of the neoplasia, the better the output of the surgical treatments employed. Besides, early detection increases the possibility of preserving the breast and decreases the probability of needing more invasive treatments [Secretaría de Salud, 2007, Alteri et al., 2011]. Mammography is currently the standard procedure employed for breast screening programs around the world. Nevertheless, its efficiency has been questioned lately because: (i) it generates many abnormal findings not related to cancer, (ii) it requires irradiating the patient and (iii) it has low specificity with dense breasts [Santen and Mansel, 2005]. Consequently, complementary techniques to mammography are being proposed to improve the detection and characterization of BC. Among these techniques, is the Ultrasound Computed Tomography (USCT), in reflection mode (which provides qualitative maps with the concentration of scatterers in the tissue), and transmission mode (which provides quantitative maps of the sound speed (SS) and the acoustic attenuation (AA) of the tissues). The images provided by the transmission modality have been proposed for BC detection as they can improve the detectability of malignancies in the breast [Mast, 2000, Duric et al., 2009]...
