A comprehensive segmentation, registration, and cancer detection scheme on 3 Tesla in vivo prostate DCE-MRI.

Satish Viswanath, B. Nicolas Bloch, Elisabeth Genega, Neil Rofsky, Robert Lenkinski, Jonathan Chappelow, Robert Toth, Anant Madabhushi

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Recently, high resolution 3 Tesla (T) Dynamic Contrast-Enhanced MRI (DCE-MRI) of the prostate has emerged as a promising modality for detecting prostate cancer (CaP). Computer-aided diagnosis (CAD) schemes for DCE-MRI data have thus far been primarily developed for breast cancer and typically involve model fitting of dynamic intensity changes as a function of contrast agent uptake by the lesion. Comparatively there is relatively little work in developing CAD schemes for prostate DCE-MRI. In this paper, we present a novel unsupervised detection scheme for CaP from 3 T DCE-MRI which comprises 3 distinct steps. First, a multi-attribute active shape model is used to automatically segment the prostate boundary from 3 T in vivo MR imagery. A robust multimodal registration scheme is then used to non-linearly align corresponding whole mount histological and DCE-MRI sections from prostatectomy specimens to determine the spatial extent of CaP. Non-linear dimensionality reduction schemes such as locally linear embedding (LLE) have been previously shown to be useful in projecting such high dimensional biomedical data into a lower dimensional subspace while preserving the non-linear geometry of the data manifold. DCE-MRI data is embedded via LLE and then classified via unsupervised consensus clustering to identify distinct classes. Quantitative evaluation on 21 histology-MRI slice pairs against registered CaP ground truth estimates yielded a maximum CaP detection accuracy of 77.20% while the popular three time point (3TP) scheme yielded an accuracy of 67.37%.

Original languageEnglish (US)
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages662-669
Number of pages8
Volume11
EditionPt 1
StatePublished - 2008

Fingerprint

Prostate
Neoplasms
Imagery (Psychotherapy)
Prostatectomy
Contrast Media
Cluster Analysis
Prostatic Neoplasms
Consensus
Histology
Breast Neoplasms

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Viswanath, S., Bloch, B. N., Genega, E., Rofsky, N., Lenkinski, R., Chappelow, J., ... Madabhushi, A. (2008). A comprehensive segmentation, registration, and cancer detection scheme on 3 Tesla in vivo prostate DCE-MRI. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Pt 1 ed., Vol. 11, pp. 662-669)

A comprehensive segmentation, registration, and cancer detection scheme on 3 Tesla in vivo prostate DCE-MRI. / Viswanath, Satish; Bloch, B. Nicolas; Genega, Elisabeth; Rofsky, Neil; Lenkinski, Robert; Chappelow, Jonathan; Toth, Robert; Madabhushi, Anant.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 11 Pt 1. ed. 2008. p. 662-669.

Research output: Chapter in Book/Report/Conference proceedingChapter

Viswanath, S, Bloch, BN, Genega, E, Rofsky, N, Lenkinski, R, Chappelow, J, Toth, R & Madabhushi, A 2008, A comprehensive segmentation, registration, and cancer detection scheme on 3 Tesla in vivo prostate DCE-MRI. in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 1 edn, vol. 11, pp. 662-669.
Viswanath S, Bloch BN, Genega E, Rofsky N, Lenkinski R, Chappelow J et al. A comprehensive segmentation, registration, and cancer detection scheme on 3 Tesla in vivo prostate DCE-MRI. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 1 ed. Vol. 11. 2008. p. 662-669
Viswanath, Satish ; Bloch, B. Nicolas ; Genega, Elisabeth ; Rofsky, Neil ; Lenkinski, Robert ; Chappelow, Jonathan ; Toth, Robert ; Madabhushi, Anant. / A comprehensive segmentation, registration, and cancer detection scheme on 3 Tesla in vivo prostate DCE-MRI. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 11 Pt 1. ed. 2008. pp. 662-669
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