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A Survey Of Ultrasonography Breast Cancer Image Segmentation Techniques
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Book Synopsis A Survey Of Ultrasonography Breast Cancer Image Segmentation Techniques by : Jwan Najeeb Saeed
Download or read book A Survey Of Ultrasonography Breast Cancer Image Segmentation Techniques written by Jwan Najeeb Saeed and published by Infinite Study. This book was released on with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most common cause of death among women globally is breast cancer. One of the key strategies to reduce mortality associated with breast cancer is to develop effective early detection techniques. The segmentation of breast ultrasound (BUS) image in Computer-Aided Diagnosis (CAD) systems is critical and challenging. Image segmentation aims to represent the image in a simplified and more meaningful way while retaining crucial features for easier analysis.
Book Synopsis Automatic Breast Ultrasound Image Segmentation: A Survey by : Min Xian
Download or read book Automatic Breast Ultrasound Image Segmentation: A Survey written by Min Xian and published by Infinite Study. This book was released on with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast cancer is one of the leading causes of cancer death among women worldwide. In clinical routine, automatic breast ultrasound (BUS) image segmentation is very challenging and essential for cancer diagnosis and treatment planning.
Book Synopsis Automated breast cancer detection and classification using ultrasound images: A survey by : H.D.Cheng
Download or read book Automated breast cancer detection and classification using ultrasound images: A survey written by H.D.Cheng and published by Infinite Study. This book was released on with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast cancer is the second leading cause of death for women all over the world. Since the cause of the disease remains unknown, early detection and diagnosis is the key for breast cancer control, and it can increase the success of treatment, save lives and reduce cost. Ultrasound imaging is one of the most frequently used diagnosis tools to detect and classify abnormalities of the breast.
Book Synopsis A Benchmark for Breast Ultrasound Image Segmentation (BUSIS) by : Min Xian
Download or read book A Benchmark for Breast Ultrasound Image Segmentation (BUSIS) written by Min Xian and published by Infinite Study. This book was released on with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast ultrasound (BUS) image segmentation is challenging and critical for BUS Computer-Aided Diagnosis (CAD) systems. Many BUS segmentation approaches have been proposed in the last two decades, but the performances of most approaches have been assessed using relatively small private datasets with different quantitative metrics, which result in discrepancy in performance comparison.
Book Synopsis Innovations in Biomedical Engineering by : Marek Gzik
Download or read book Innovations in Biomedical Engineering written by Marek Gzik and published by Springer Nature. This book was released on 2022-05-31 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest developments in the field of biomedical engineering and includes practical solutions and strictly scientific considerations. The development of new methods of treatment, advanced diagnostics or personalized rehabilitation requires close cooperation of experts from many fields, including, among others, medicine, biotechnology and finally biomedical engineering. The latter, combining many fields of science, such as computer science, materials science, biomechanics, electronics not only enables the development and production of modern medical equipment, but also participates in the development of new directions and methods of treatment. The presented monograph is a collection of scientific papers on the use of engineering methods in medicine. The topics of the work include both practical solutions and strictly scientific considerations expanding knowledge about the functioning of the human body. We believe that the presented works will have an impact on the development of the field of science, which is biomedical engineering, constituting a contribution to the discussion on the directions of development of cooperation between doctors, physiotherapists and engineers. We would also like to thank all the people who contributed to the creation of this monograph—both the authors of all the works and those involved in technical works.
Book Synopsis A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images by : YaozhongLuo
Download or read book A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images written by YaozhongLuo and published by Infinite Study. This book was released on with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ultrasound imaging has become one of the most popular medical imaging modalities with numerous diagnostic applications. However, ultrasound (US) image segmentation, which is the essential process for further analysis, is a challenging task due to the poor image quality.
Book Synopsis A Fully Automatic Segmentation Method for Breast Ultrasound Images by : Juan Shan
Download or read book A Fully Automatic Segmentation Method for Breast Ultrasound Images written by Juan Shan and published by . This book was released on 2011 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast cancer is the second leading cause of death of women worldwide. Accurate lesion boundary detection is important for breast cancer diagnosis. Since many crucial features for discriminating benign and malignant lesions are based on the contour, shape, and texture of the lesion, an accurate segmentation method is essential for a successful diagnosis. Ultrasound is an effective screening tool and primarily useful for differentiating benign and malignant lesions. However, due to inherent speckle noise and low contrast of breast ultrasound imaging, automatic lesion segmentation is still a challenging task. This research focuses on developing a novel, effective, and fully automatic lesion segmentation method for breast ultrasound images. By incorporating empirical domain knowledge of breast structure, a region of interest is generated. Then, a novel enhancement algorithm (using a novel phase feature) and a newly developed neutrosophic clustering method are developed to detect the precise lesion boundary. Neutrosophy is a recently introduced branch of philosophy that deals with paradoxes, contradictions, antitheses, and antinomies. When neutrosophy is used to segment images with vague boundaries, its unique ability to deal with uncertainty is brought to bear. In this work, we apply neutrosophy to breast ultrasound image segmentation and propose a new clustering method named neutrosophic l-means. We compare the proposed method with traditional fuzzy c-means clustering and three other well-developed segmentation methods for breast ultrasound images, using the same database. Both accuracy and time complexity are analyzed. The proposed method achieves the best accuracy (TP rate is 94.36%, FP rate is 8.08%, and similarity rate is 87.39%) with a fairly rapid processing speed (about 20 seconds). Sensitivity analysis shows the robustness of the proposed method as well. Cases with multiple-lesions and severe shadowing effect (shadow areas having similar intensity values of the lesion and tightly connected with the lesion) are not included in this study.
Book Synopsis Ultrasound Image Classification and Segmentation Using Deep Learning Applications by : Umar Farooq Mohammad
Download or read book Ultrasound Image Classification and Segmentation Using Deep Learning Applications written by Umar Farooq Mohammad and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast cancer is one of the most common diseases with a high mortality rate. Early detection and diagnosis using computer-aided methods is considered one of the most efficient ways to control the mortality rate. Different types of classical methods were applied to segment the region of interest from breast ultrasound images. In recent years, Deep learning (DL) based implementations achieved state-of-the-art results for various diseases in both accuracy and inference speed on large datasets. We propose two different supervised learning-based approaches with adaptive optimization methods to segment breast cancer tumours from ultrasound images. The first approach is to switch from Adam to Stochastic Gradient Descent (SGD) in between the training process. The second approach is to employ an adaptive learning rate technique to achieve a rapid training process with element-wise scaling in terms of learning rates. We have implemented our algorithms on four state-of-the-art architectures like AlexNet, VGG19, Resnet50, U-Net++ for the segmentation task of the cancer lesion in the breast ultrasound images and evaluate the Intersection Over Union (IOU) of the four aforementioned architectures using the following methods : 1) without any change, i.e., SGD optimizer, 2) with the substitution of Adam with SGD after three quarters of the total epochs and 3) with adaptive optimization technique. Despite superior training performances of recent DL-based applications on medical ultrasound images, most of the models lacked generalization and could not achieve higher accuracy on new datasets. To overcome the generalization problem, we introduce semi-supervised learning methods using transformers, which are designed for sequence-to-sequence prediction. Transformers have recently emerged as a viable alternative to natural global self-attention processes. However, due to a lack of low-level information, they may have limited translation abilities. To overcome this problem, we created a network that takes advantages of both transformers and UNet++ architectures. Transformers uses a tokenized picture patch as the input sequence for extracting global contexts from a Convolution Neural Network (CNN) feature map. To achieve exact localization, the decoder upsamples the encoded features, which are subsequently integrated with the high-resolution CNN feature maps. As an extension of our implementation, we have also employed the adaptive optimization approach on this architecture to enhance the capabilities of segmenting the breast cancer tumours from ultrasound images. The proposed method achieved better outcomes in comparison to the supervised learning based image segmentation algorithms.
Book Synopsis An Automatic System for Classification of Breast Cancer Lesions in Ultrasound Images by : Behnam Karimi
Download or read book An Automatic System for Classification of Breast Cancer Lesions in Ultrasound Images written by Behnam Karimi and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Research and Development in Breast Ultrasound by : E. Ueno
Download or read book Research and Development in Breast Ultrasound written by E. Ueno and published by Springer Science & Business Media. This book was released on 2006-03-20 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was planned in order to announce the contents discussed in the 13th International Congress on the Ultrasound Examination of the Breast. Breast ultrasound has become a indispensable method for the diagnosis of cancer of the breast. Breast ultrasound will become more convenient and precise diagnostic method according to the development of the device. In addition, application to breast screening or medical check has started, on the other hand the interventional method has also developed.
Book Synopsis Mammography and Beyond by : National Research Council
Download or read book Mammography and Beyond written by National Research Council and published by National Academies Press. This book was released on 2001-06-04 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: X-ray mammography screening is the current mainstay for early breast cancer detection. It has been proven to detect breast cancer at an earlier stage and to reduce the number of women dying from the disease. However, it has a number of limitations. These current limitations in early breast cancer detection technology are driving a surge of new technological developments, from modifications of x-ray mammography such as computer programs that can indicate suspicious areas, to newer methods of detection such as magnetic resonance imaging (MRI) or biochemical tests on breast fluids. To explore the merits and drawbacks of these new breast cancer detection techniques, the Institute of Medicine of the National Academy of Sciences convened a committee of experts. During its year of operation, the committee examined the peer-reviewed literature, consulted with other experts in the field, and held two public workshops. In addition to identifying promising new technologies for early detection, the committee explored potential barriers that might prevent the development of new detection methods and their common usage. Such barriers could include lack of funding from agencies that support research and lack of investment in the commercial sector; complicated, inconsistent, or unpredictable federal regulations; inadequate insurance reimbursement; and limited access to or unacceptability of breast cancer detection technology for women and their doctors. Based on the findings of their study, the committee prepared a report entitled Mammography and Beyond: Developing Technology for Early Detection of Breast Cancer, which was published in the spring of 2001. This is a non-technical summary of that report.
Book Synopsis Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support by : M. Jorge Cardoso
Download or read book Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support written by M. Jorge Cardoso and published by Springer. This book was released on 2017-09-07 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.
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 Computer-aided Detection of Breast Cancer Using Ultrasound Images by : Yanhui Guo
Download or read book Computer-aided Detection of Breast Cancer Using Ultrasound Images written by Yanhui Guo and published by . This book was released on 2010 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ultrasound imaging suffers from severe speckle noise. We propose a novel approach for speckle reduction using 2D homogeneity and directional average filters to remove speckle noise. We transform speckle noise into additive noise using a logarithm transformation. Texture information is employed to describe the speckle characteristics of the image. The homogeneity value is defined using texture information value, and the ultrasound image is transformed into a homogeneity domain from the gray domain. If the homogeneity value is high, the region is homogenous and has less speckle noise. Otherwise, the region is nonhomogenous, and speckle noise occurs. The threshold value is employed to distinguish homogenous regions from regions with speckle noise obtained from a 2D homogeneity histogram according to the maximal entropy principle. A new directional filtering is convoluted to remove noise from pixels in a nonhomogenous region. The filtering processing iterates until the breast ultrasound image is homogenous enough. Experiments show the proposed method improves denoising and edge-preserving capability. We present a novel enhancement algorithm based on fuzzy logic to enhance the fine details of ultrasound image features, while avoiding noise amplification and overenhancement. We take into account both the fuzzy nature of an ultrasound and feature regions on images, which are significant in diagnosis. The maximal entropy principle utilizes the gray-level information to map the image into fuzzy domain. Edge and textural information is extracted in fuzzy domain to describe the features of lesions. The contrast ratio is computed and modified by the local information. Finally, the defuzzification operation transforms the enhanced ultrasound images back to the spatial domain. Experimental results confirm a high enhancement performance including fine details of lesions, without over- or under-enhancement. Identifying object boundaries in ultrasound images is a difficult task. We present a novel automatic segmentation algorithm based on characteristics of breast tissue and eliminating particle swarm optimization (EPSO) clustering analysis, thus transforming the segmentation problem into clustering analysis. Mammary gland characteristics in ultrasound images are utilized, and a step-down threshold technique is employed to locate the mammary gland area. Experimental results demonstrate that the proposed approach increases clustering speed and segments the mass from tissue background with high accuracy.
Book Synopsis Advances in Diagnostic and Therapeutic Ultrasound Imaging by : Jasjit S. Suri
Download or read book Advances in Diagnostic and Therapeutic Ultrasound Imaging written by Jasjit S. Suri and published by Artech House. This book was released on 2008 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This groundbreaking resource offers you exclusive coverage of the latest techniques in diagnostic and therapeutic 3-D ultrasound imaging instrumentation and techniques. Providing a solid overview of potential applications in clinical practice, you find need-to-know details on major diseases, including vascular diseases, breast cancer, cardiac abnormalities and prostate cancer.
Book Synopsis Contrast-Enhanced Mammography by : Marc Lobbes
Download or read book Contrast-Enhanced Mammography written by Marc Lobbes and published by Springer. This book was released on 2019-04-29 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive guide to contrast-enhanced mammography (CEM), a novel advanced mammography technique using dual-energy mammography in combination with intravenous contrast administration in order to increase the diagnostic performance of digital mammography. Readers will find helpful information on the principles of CEM and indications for the technique. Detailed attention is devoted to image interpretation, with presentation of case examples and highlighting of pitfalls and artifacts. Other topics to be addressed include the establishment of a CEM program, the comparative merits of CEM and MRI, and the roles of CEM in screening populations and monitoring of response to neoadjuvant chemotherapy. CEM became commercially available in 2011 and is increasingly being used in clinical practice owing to its superiority over full-field digital mammography. This book will be an ideal source of knowledge and guidance for all who wish to start using the technique or to learn more about it.
Book Synopsis Improved Mammographic Technique for Breast Cancer Diagnosis by :
Download or read book Improved Mammographic Technique for Breast Cancer Diagnosis written by and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the entire project period, we have completed the following tasks: (1) Develop computerized breast border detection and classification scheme. (2) Develop and evaluate exposure equalization filters. (3) Monte Carlo modeling of mammographic imaging systems and optimization of imaging techniques. (4) Design and build breast-tissue-equivalent phantoms for x-ray and ultrasound imaging. (5) Evaluate effects of equalization on image quality. (6) Develop a novel combined x-ray equalization and ultrasound imaging system for improved evaluation of dense breasts and mammographic lesions. (7) Design and build a compressible tank and a special compression paddle for combined imaging. (8) Evaluate tissue-equivalent fluids for x-ray equalization and ultrasound coupling. (9) Perform phantom study to evaluate the feasibility of combined imaging. (10) Develop breast density segmentation program for automated localization of dense tissue regions on digitized mammograms. (11) Design and build a prototype motorized ultrasound scanning device for the combined imaging system. These studies are consistent with the goals of our proposed project. Our new approach of using a compressible tank containing tissue-equivalent fluid for x%ay equalization in a prone mammography system provides truly patient-specific equalization for breasts of any size and shape, and for any mammographic view. Our studies indicate that x-ray equalization can improve visibility of breast lesions on mammograms. We also demonstrated that the feasibility of developing a combined x-ray and ultrasound imaging system for improved breast imaging. The capability of allowing ultrasound scanning in the same geometry as mammography has the promise to improve breast cancer detection and diagnosis in dense breasts.
