Usefulness of Collaborative Work in the Evaluation of Prostate Cancer from MRI

Abstract

The aim of this study is to show the usefulness of collaborative work in the evaluation of prostate cancer from T2-weighted MRI using a dedicated software tool. The variability of annotations on images of the prostate gland (central and peripheral zones as well as tumour) by two independent experts was firstly evaluated, and secondly compared with a consensus between these two experts. Using a prostate MRI database, experts drew regions of interest (ROIs) corresponding to healthy prostate (peripheral and central zones) and cancer. One of the experts then drew the ROI with knowledge of the other expert’s ROI. The surface area of each ROI was used to measure the Hausdorff distance and the Dice coefficient was measured from the respective contours. They were evaluated between the different experiments, taking the annotations of the second expert as the reference. The results showed that the significant differences between the two experts disappeared with collaborative work. To conclude, this study shows that collaborative work with a dedicated tool allows consensus between expertise in the evaluation of prostate cancer from T2-weighted MRI.

Semi-Automatic GUI Platform to Characterize Brain Development in Preterm Children Using Ultrasound Images

“…In the medical field, image segmentation plays a crucial role in achieving precise analysis of anatomical data. This involves extracting desired objects from medical images (2D or 3D), which can be accomplished manually, semi-automatically, or fully automatically [19][20][21]. The integration of artificial intelligence techniques provides various solutions.…”