The Current Status and Likely Future of Breast Imaging CAD
Jasjit S Suri; Ramachandran Chandrasekhar; Nico Lanconelli; Renato Campanini; Matteo Roffilli; Ruey-Feng Chang; Yujun Guo; Radhika Sivaramakrishna; Tibor Tot; Begona Acha; Carmen Serrano; Ingrid Reiser; Robert M Nishikawa; Dee H Wu; Koon-Pong Wong; Ashwini Kshirsagar; Yajie Sun; Michael Wirth; Aize Cao; J E Leo Desautels; Rangaraj M Rangayyan
DOI: 10.1117/3.651880.ch28
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Excerpt

28.1 Introduction

In this chapter, the present status and future possibilities for computer-aided-detection (CAD) in breast imaging is considered. Xeromammography and later, conventional x-ray mammography, were among the earliest medical imaging modalities to benefit from the use of computers to assist radiologists in detecting lesions, especially cancers.

At present, mammography is the preferred method to screen asymptomatic women for breast cancer. Breast cancer itself is a heterogeneous disease with no cure; the earlier the cancer is detected, the better the prognosis. The principal thrust of CAD research in recent years has therefore been to detect early signs of the disease, such as microcalcifications, small masses, and subtle lesions, especially those most likely to be missed by radiologists, so that any cancer present may be detected at the earliest possible stage of the disease.

In this chapter, CAD in breast imaging is reviewed, and the possible lines of future research and development speculated on. The major unresolved problems are identified and, in some cases, promising trends and possible solutions are outlined. Mammography has certain structural deficiencies that have propelled research into alternative imaging modalities for breast cancer detection. Some of these emerging imaging modalities that could either be adjuncts to mammography or supplant it in the future are reviewed. The possible roles for CAD for these alternative modalities are also examined. Certain generic problems of CAD, such as accurate segmentation, registration, lesion detection, and assessment of algorithm performance are then considered.

The technology of CAD, in the context of mammography, generally stands for computer-aided detection of lesions and suspicious regions, meriting careful scrutiny by a radiologist. If a patient's history and the radiologist's findings are taken into account, together with the computer-aided detection data that provides diagnostic output, a computer-aided diagnosis (CADx) system exists. Sometimes, a computer-aided diagnosis system is also confusingly referred to by the acronym CAD. In an attempt to overcome such confusion, a computer-aided detection system is sometimes referred to as a CADe system. In this chapter, computer-aided detection is referred to as CAD, and computer-aided diagnosis as CADx.

The initial steps in CAD include image segmentation to identify the extent of the breast region and possible image registration to match the image with its contralateral or temporal pair. Lesion detection begins with analysis of the image using feature vectors to identify regions of geographic singularity. Lesion detection is completed by feature extraction, feature selection, and classification. Finally, validation by testing the system on different, sufficiently large data sets is necessary to determine system performance and robustness. If, in addition, radiologist findings and patient history are incorporated into the system, a CADx system results.

© 2006 Society of Photo-Optical Instrumentation Engineers

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