By Holger R. Roth, Thomas E. Hampshire, Jamie R. McClelland, Mingxing Hu, Darren J. Boone (auth.), Hiroyuki Yoshida, Georgios Sakas, Marius George Linguraru (eds.)
This booklet constitutes the completely refereed post-conference court cases of the 3rd overseas Workshop on Computational and scientific functions in stomach Imaging, held along with MICCAI 2011, in Toronto, Canada, on September 18, 2011. The 33 revised complete papers provided have been rigorously reviewed and chosen from forty submissions. The papers are prepared in topical sections on digital colonoscopy and CAD, belly intervention, and computational stomach anatomy.
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Additional info for Abdominal Imaging. Computational and Clinical Applications: Third International Workshop, Held in Conjunction with MICCAI 2011, Toronto, ON, Canada, September 18, 2011, Revised Selected Papers
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For an unseen sample, the RF classiﬁer is tested by propagation of the sample through each tree. The predictions by the trees are aggregated into an RF prediction by majority vote. J. N¨ appi, D. Regge, and H. Yoshida Fig. 2. 3 The CAD System The CAD system is fully automated. A thick region encompassing the colonic mucosa is extracted automatically from input CTC data . Volumetric shape features are calculated within the extracted region, and lesion candidates are detected by hysteresis thresholding of the shape features .
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