A new partial volume segmentation approach to extract bladder wall for computer aided detection in virtual cystoscopy

Lihong Li, Zigang Wang, Xiang Li, Xinzhou Wei, Howard L. Adler, Wei Huang, Syed Rizvi, Hong Meng, Donald P. Harrington, Zhengrong Liang

Research output: Contribution to journalConference articlepeer-review

16 Scopus citations


Image Processing and Computer Vision Research Laboratory, Department of Engineering Science and Physics, College of Staten Island, City University of New York, Staten Island, NY 10314 We propose a new partial volume (PV) segmentation scheme to extract bladder wall for computer aided detection (CAD) of bladder lesions using multispectral MR images. Compared with CT images, MR images provide not only a better tissue contrast between bladder wall and bladder lumen, but also the multispectral information. As multispectral images are spatially registered over three-dimensional space, information extracted from them is more valuable than that extracted from each image individually. Furthermore, the intrinsic T 1 and T 2 contrast of the urine against the bladder wall eliminates the invasive air insufflation procedure. Because the earliest stages of bladder lesion growth tend to develop gradually and migrate slowly from the mucosa into the bladder wall, our proposed PV algorithm quantifies images as percentages of tissues inside each voxel. It preserves both morphology and texture information and provides tissue growth tendency in addition to the anatomical structure. Our CAD system utilizes a multi-scan protocol on dual (full and empty of urine) states of the bladder to extract both geometrical and texture information. Moreover, multi-scan of transverse and coronal MR images eliminates motion artifacts. Experimental results indicate that the presented scheme is feasible towards mass screening and lesion detection for virtual cystoscopy (VC).

Original languageEnglish (US)
Pages (from-to)199-206
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2004
Externally publishedYes
EventMedical Imaging 2004: Physiology, Function, and Structure from Medical Images - San Diego, CA, United States
Duration: Feb 15 2004Feb 17 2004


  • Computer aided detection
  • Mri-based virtual cystoscopy
  • Non-invasive screening
  • Partial volume segmentation
  • Virtual endoscopy

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


Dive into the research topics of 'A new partial volume segmentation approach to extract bladder wall for computer aided detection in virtual cystoscopy'. Together they form a unique fingerprint.

Cite this