By Robin N. Strickland
Univ. of Arizona, Tucson. presents a present overview of laptop processing algorithms for the identity of lesions, irregular plenty, melanoma, and sickness in scientific photos. offers examples from a number of imaging modalities for higher acceptance of anomalies in MRI, CT, SPECT, and digital/film X ray.
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Extra resources for Image-Processing Techniques for Tumor Detection
The term “gold standard” is sometimes used to mean essentially the same thing. Defining ground truth in biological systems is often complicated. Although applications related to remote sensing, for Copyright © 2002 Marcel Dekker, Inc. , assessment of most disease processes and symptoms are not always defined in absolute terms. This is particularly applicable to medical image interpretation. For tumor detection in medical images, ground truth typically would refer to the pathology results from biopsy specimens.
This is due in part to inadequate or small Copyright © 2002 Marcel Dekker, Inc. data sets at the research stage, inconsistent evaluation criteria, and optimistic train/test formulations. To whatever extent possible, the test data should be typical of what could be expected in a real-world environment. This applies with respect to the subtlety of the tumors, variability of image quality, and overall appearance of the images. For example, mammogram images exhibit a wide variety of breast tissue densities and textures.
17. 18. 19. 20. 21. American College of Radiology. Breast Imaging Reporting and Data System (BIRADS), May 1993. J Suckling, J Parker, DR Dance, S Astley, I Hutt, CRM Boggis, I Ricketts, E Stamatakis, N Cerneaz, SL Kok, P Taylor, D Betal, J Savage. The mammographic image analysis society digital mammogram database. Proceedings of the 2nd International Workshop on Digital Mammography. York, England: Elsevier Science, 1994, pp 375–378. LN Mascio, SD Frankel, JM Hernandez, CM Logan. Building the LLNL/UCSF digital mammogram library with image groundtruth.