By Robin N. Strickland
Univ. of Arizona, Tucson. offers a present assessment of desktop processing algorithms for the id of lesions, irregular plenty, melanoma, and ailment in clinical pictures. provides examples from various 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
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Comparison of objective methods of scoring computer-detected microcalcification clusters in mammograms. Radiol Soc North Am 205(P):217, 1997. KS Woods, CC Doss, KW Bowyer, JL Solka, CE Priebe, WP Kegelmeyer, Jr. Comparative evaluation of pattern recognition techniques for detection of microcalcifications in mammography. Int J Pattern Recognition Artif Intell 7:1417–1436, 1993. N Karssemeijer, GM te Brake. Detection of stellate distortions in mammograms. IEEE Trans Med Imaging 15:611–619, 1996. W Kegelmeyer, J Pruneda, P Bourland, A Hillis, M Riggs, M Nipper.
The only difference between methods A and B is a preprocessing step for estimating the image noise level. All other parts of the algorithm are identical. So, this experiment clearly isolates the effect of two variations of a preprocessing step and justifies the selection of method B. The FROC analysis also permits us to specify the operating sensitivity of the segmentation module by means of selection of an appropriate threshold for the filtered image. Because we would like approximately 90% sensitivity, we simply need to select the threshold that generated the operating point closest to this desired performance.
V, we summarize what we believe to be the essential aspects of a sound evaluation and make some basic recommendations. Finally, in Sec. VI, we use a case study to illustrate many of the concepts and techniques discussed in this chapter. II. DETECTION CRITERIA Perhaps the first issue to deal with concerns the characterization of a computer detection as either true positive or false positive. To do this for a given image, the output of the computer algorithm must be compared with the “ground truth” information associated with the image.