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Languages : en
Pages : 58
Book Description
The goal of this project is to demonstrate the clinical usefulness of computer-aided diagnosis (CAD) in mammographic detection of breast cancer. Our plan is to develop advanced CAD schemes for detection and characterization of clustered microcalcifications and masses by incorporating artificial neural networks and various image processing techniques. Clinical mammography workstations for automated detection of suspicious lesions in mammograms will be developed by integration of laser digitizer, high-speed computer-and advanced CAD software. The prototype workstations will be used as a "second opinion in interpreting mammograms by reducing observational errors. The outcomes of radiologists' image readings in the detection of breast cancer will be evaluated by examining radiologists' performance when reading films only and when reading film with the computer results. we believe that the outcomes of this demonstration project will lead to large-scale clinical trials and will result in commercial projects for practical routine use in breast imaging.
