Automated Breast Cancer Detection And Classification Using Ultrasound Images A Survey

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.

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.

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.

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.

The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography

Elastography, the science of creating noninvasive images of mechanical characteristics of tissues, has been rapidly evolving in recent years. The advantage of this technique resides in the ability to rapidly detect and quantify the changes in the stiffness of soft tissues resulting from specific pathological or physiological processes. Ultrasound elastography is nowadays applied especially on the liver and breast, but the technique has been increasingly used for other tissues including the thyroid, lymph nodes, spleen, pancreas, gastrointestinal tract, kidney, prostate, and the musculoskeletal and vascular systems. This book presents some of the applications of strain and shear-wave ultrasound elastography in hepatic, pancreatic, breast, and musculoskeletal conditions.

Early detection of breast cancer with screening mammography is still the best method we have in saving countless women's lives and decreasing the harms of overtreatment. This textbook encompasses relevant topics in daily patient care with breast imaging to technical innovations for improving breast cancer detection and treatment.