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Tumor Detection in the Bladder Wall with a Measurement of Abnormal Thickness in CT Scans
Institution:
 Telecommunications Laboratory, Université Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium. jaume@tele.ucl.ac.be
Publisher:
 IEEE Trans Biomed Eng
Publication Date:
 Mar-2003
Volume Number:
 50
Issue Number:
 3
Pages:
 383-390
Citation:
 IEEE Trans Biomed Eng. 2003 Mar;50(3):383-90.
PubMed ID:
 12669995
Keywords:
 Anatomical atlas, bladder wall, computer-aided diagnosis, thickness measurement, tumor detection, virtual cystoscopy, virtual endoscopy
Appears in Collections:
SPL, CRL, NAC
Sponsors:
 NIH P01 CA67165
NIH P41 RR13218
NIH R01 RR11747
NIH R01 EB000304
NIH R21 CA80945-01
Generated Citation:
 Jaume S., Ferrant M., Macq B., Hoyte L., Fielding J.R., Schreyer A., Kikinis R., Warfield S.K. Tumor Detection in the Bladder Wall with a Measurement of Abnormal Thickness in CT Scans. IEEE Trans Biomed Eng. 2003 Mar;50(3):383-90. PMID: 12669995.
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Virtual cystoscopy is a developing technique for bladder cancer screening. In a conventional cystoscopy, an optical probe is inserted into the bladder and an expert reviews the appearance of the bladder wall. Physical limitations of the probe place restrictions on the examination of the bladder wall. In virtual cystoscopy, a computed tomography (CT) scan of the bladder is acquired and an expert reviews the appearance of the bladder wall as shown by the CT. The task of identifying tumors in the bladder wall has often been done without extensive computational aid to the expert. We have developed an image processing algorithm that aids the expert in the detection of bladder tumors. Compared with an expert observer reading the CT, our algorithm achieves 89% sensitivity, 88% specificity, 48% positive predictive value, and 98% negative predictive value.

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