Sequential Registration-Based Segmentation of the Prostate Gland in MR Image Volumes.
Accurate and fast segmentation and volume estimation of the prostate gland in magnetic resonance (MR) images are necessary steps in the diagnosis, treatment, and monitoring of prostate cancer. This paper presents an algorithm for the prostate gland volume estimation based on the semi-automated segme...
| Published in: | Journal of Digital Imaging Vol. 29; no. 2; pp. 254 - 264 |
|---|---|
| Main Authors: | , , , , |
| Format: | equations & formulas research tables/charts Journal Article |
| Published: |
Springer Nature
Apr2016
|
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=113705629&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 113705629 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Apr2016 vid: 29 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 113705629 113705629 113705629 10.1007/s10278-015-9844-y 113705629 ppf: 254 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Sequential Registration-Based Segmentation of the Prostate Gland in MR Image Volumes. aug: au: Khalvati, Farzad Salmanpour, Aryan Rahnamayan, Shahryar Haider, Masoom Tizhoosh, H. affil: Department of Electrical, Computer and Software Engineering, University of Ontario Institute of Technology, Oshawa Canada sug: subj: Prostate Radiography Magnetic Resonance Imaging Algorithms Image Processing, Computer Assisted Methods Comparative Studies Human ab: Accurate and fast segmentation and volume estimation of the prostate gland in magnetic resonance (MR) images are necessary steps in the diagnosis, treatment, and monitoring of prostate cancer. This paper presents an algorithm for the prostate gland volume estimation based on the semi-automated segmentation of individual slices in T2-weighted MR image sequences. The proposed sequential registration-based segmentation (SRS) algorithm, which was inspired by the clinical workflow during medical image contouring, relies on inter-slice image registration and user interaction/correction to segment the prostate gland without the use of an anatomical atlas. It automatically generates contours for each slice using a registration algorithm, provided that the user edits and approves the marking in some previous slices. We conducted comprehensive experiments to measure the performance of the proposed algorithm using three registration methods (i.e., rigid, affine, and nonrigid). Five radiation oncologists participated in the study where they contoured the prostate MR (T2-weighted) images of 15 patients both manually and using the SRS algorithm. Compared to the manual segmentation, on average, the SRS algorithm reduced the contouring time by 62 % (a speedup factor of 2.64×) while maintaining the segmentation accuracy at the same level as the intra-user agreement level (i.e., Dice similarity coefficient of 91 versus 90 %). The proposed algorithm exploits the inter-slice similarity of volumetric MR image series to achieve highly accurate results while significantly reducing the contouring time. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|