Computer-aided detection and classification of microcalcifications in mammograms: a survey

Mammary tumors similar to those observed in women can be induced in rats by intraperitoneal administration of N-methyl-N-nitrosourea. Determining tumor volume is a useful and quantitative way to monitor tumor progression. In this study, the authors measured dimensions of rat mammary tumors using a caliper and using real-time compound B-mode ultrasonography. They then used different formulas to calculate tumor volume from these tumor measurements and compared the calculated tumor volumes with the real tumor volume to identify the formulas that gave the most accurate volume calculations. They found that caliper and ultrasonography measurements were significantly correlated but that tumor volumes calculated using different formulas varied substantially. Mammary tumors seemed to take on an oblate spheroid geometry. The most accurate volume calculations were obtained using the formula V = (W(2) × L)/2 for caliper measurements and the formula V = (4/3) × π × (L/2) × (L/2) × (D/2) for ultrasonography measurements, where V is tumor volume, W is tumor width, L is tumor length and D is tumor depth.

Estimation of rat mammary tumor volume using caliper and ultrasonography measurements.

A Fuzzy C-Means (FCM)-Based Approach for Computerized Segmentation of Breast Lesions in Dynamic Contrast-Enhanced MR Images1

/pdf/computer-aided-detection-and-diagnosis-in-mammography-4exig6gc0f.pdf

Computer-Aided Detection and Diagnosis in Mammography

The roles of physicists in medical imaging have expanded over the years, from the study of imaging systems (sources and detectors) and dose to the assessment of image quality and perception, the development of image processing techniques, and the development of image analysis methods to assist in detection and diagnosis. The latter is a natural extension of medical physicists' goals in developing imaging techniques to help physicians acquire diagnostic information and improve clinical decisions. Studies indicate that radiologists do not detect all abnormalities on images that are visible on retrospective review, and they do not always correctly characterize abnormalities that are found. Since the 1950s, the potential use of computers had been considered for analysis of radiographic abnormalities. In the mid-1980s, however, medical physicists and radiologists began major research efforts for computer-aided detection or computer-aided diagnosis (CAD), that is, using the computer output as an aid to radiologists-as opposed to a completely automatic computer interpretation-focusing initially on methods for the detection of lesions on chest radiographs and mammograms. Since then, extensive investigations of computerized image analysis for detection or diagnosis of abnormalities in a variety of 2D and 3D medical images have been conducted. The growth of CAD over the past 20 years has been tremendous-from the early days of time-consuming film digitization and CPU-intensive computations on a limited number of cases to its current status in which developed CAD approaches are evaluated rigorously on large clinically relevant databases. CAD research by medical physicists includes many aspects-collecting relevant normal and pathological cases; developing computer algorithms appropriate for the medical interpretation task including those for segmentation, feature extraction, and classifier design; developing methodology for assessing CAD performance; validating the algorithms using appropriate cases to measure performance and robustness; conducting observer studies with which to evaluate radiologists in the diagnostic task without and with the use of the computer aid; and ultimately assessing performance with a clinical trial. Medical physicists also have an important role in quantitative imaging, by validating the quantitative integrity of scanners and developing imaging techniques, and image analysis tools that extract quantitative data in a more accurate and automated fashion. As imaging systems become more complex and the need for better quantitative information from images grows, the future includes the combined research efforts from physicists working in CAD with those working on quantitative imaging systems to readily yield information on morphology, function, molecular structure, and more-from animal imaging research to clinical patient care. A historical review of CAD and a discussion of challenges for the future are presented here, along with the extension to quantitative image analysis.

https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1118/1.3013555

Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.

Background: Accurate measurement of the size of breast cancers becomes more important as breast cancer therapy advances. This study reports the accuracy of magnetic resonance imaging (MRI), ultrasonography and mammography for measuring the largest breast cancer diameter in comparison to the pathology measurement.

Breast cancer measurements with magnetic resonance imaging, ultrasonography, and mammography

Computer-aided detection of clustered microcalcifications in digitized mammograms

An occult breast cancer was detected and wire localization performed using magnetic resonance imaging.

Magnetic resonance imaging detection and wire localization of an 'occult' breast cancer.

Selection of processing algorithms for digital image compression: A rank-order study

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Papers

Breast cancer measurements with magnetic resonance imaging, ultrasonography, and mammography

Computer-aided detection of clustered microcalcifications in digitized mammograms

Magnetic resonance imaging detection and wire localization of an 'occult' breast cancer.

Selection of processing algorithms for digital image compression: A rank-order study