Abstract
Breast cancer is a familiar disease in the female; its effects are, however, not so much diverse in males. In females, the death rate is gradually increasing due to this disease because rarely its sign and symptoms appear at an initial phase that makes it hard to detect at an early stage. As breast cancer has developed into the rapidly growing disease among women, numerous detection methods, algorithms and new technologies and machinery are introduced in the market for its early detection. Computer aided diagnosis and detection system proved to be an efficient tool for early detection of breast tumor. Various techniques have been presented by researchers for the improved performance of CAD systems for diagnosis/detection of breast masses. The aim of this rese arch work is to present a concise review of different imaging modalities and techniques with their performance assessment in different stages of an automated or computer aided detection system (CAD) for breast tumor detection. The most commonly used imaging modalities are discussed like mammography, MRI, and ultrasound for breast cancer detection and diagnostic purposes. A detailed discussion of different imaging modalities, datasets, performance measures and various techniques used for the automated detection of a breast tumor with recent advances and evaluation of their performance in different steps of computer-aided diagnosis and detection systems is presented here.
Keywords: Benign, CAD, imaging modalities mammograms, MR images, malignant, US images.
Graphical Abstract
Call for Papers in Thematic Issues
Advancements and Applications of Photon Counting CT: Transforming Imaging Precision and Quantification
Photon Counting Computed Tomography (CT) represents a transformative advancement in medical imaging technology, offering unprecedented levels of precision and diagnostic capability. This special issue will explore the latest innovations and applications of photon counting CT, highlighting its advantages over traditional energy-integrating detectors. The scope includes an in-depth examination of its ...read more
Advancements in Deep Learning based Medical Image and Signal Processing for Healthcare Applications
The accurate predication from medical data (signals and images) analytics will be achieved through the use of cutting-edge AI tools for tailoring medical treatment to each patient. When the agents are done analysing the user's health data, the user can consult with the agents to receive advice and the most ...read more
AI-Driven Diagnostics in Radiology and Medical Imaging
Medical imaging data, such as X-rays, MRIs, ultrasounds, CT scans, and DXAs, can be analysed by AI algorithms to help healthcare professionals identify and diagnose diseases more rapidly and accurately. Among the most cutting-edge applications of artificial intelligence (AI) in healthcare are imaging-related applications like cancer detection. AI could revolutionise ...read more
Applying medical image processing techniques for early cancer detection in mammograms
Breast cancer survival and successful treatment are significantly boosted by early identification. Breast cancer screening is most commonly accomplished with mammography. The radiologist's experience and the image quality, among several other factors, might affect how well a mammogram is interpreted. Enhancing mammography analysis and increasing cancer early detection are made ...read more
38