Obtaining accurate segmentation of the prostate and nearby organs at risk (e.g., bladder and rectum) in CT images is critical for radiotherapy of prostate cancer. Currently, the leading automatic segmentation algorithms are based on Fully Convolutional Networks (FCNs), which achieve remarkable performance but usually need large-scale datasets with high-quality voxel-wise annotations for full supervision of the training. Unfortunately, such annotations are difficult to acquire, which becomes a bottleneck to build accurate segmentation models in real clinical applications. In this paper, we propose a novel weakly supervised segmentation approach that only needs 3D bounding box annotations covering the organs of interest to start the training. Obviously, the bounding box includes many non-organ voxels that carry noisy labels to mislead the segmentation model. To this end, we propose the label denoising module and embed it into the iterative training scheme of the label denoising network (LDnet) for segmentation. The labels of the training voxels are predicted by the tentative LDnet, while the label denoising module identifies the voxels with unreliable labels. As only the good training voxels are preserved, the iteratively re-trained LDnet can refine its segmentation capability gradually. Our results are remarkable, i.e., reaching ~94% (prostate), ~91% (bladder), and ~86% (rectum) of the Dice Similarity Coefficients (DSCs), compared to the case of fully supervised learning upon high-quality voxel-wise annotations and also superior to several state-of-the-art approaches. To our best knowledge, this is the first work to achieve voxel-wise segmentation in CT images from simple 3D bounding box annotations, which can greatly reduce many labeling efforts and meet the demands of the practical clinical applications.
February 4, 2020
Maternal Undernourishment in Guinea Pigs Leads to Fetal Growth Restriction with Increased Hypoxic Cells and Oxidative Stress in the Brain.
April 22, 2020
- ASCO – Lung CancerASCO.20 Virtual Scientific Program, held May 29 - 31, brought professionals from all over the world together to hear the brightest minds in oncology present state-of-the-art treatment modalities and new therapies.
- AACR-2020The American Association for Cancer Research is the world's oldest and largest professional association related to cancer research.
- ACC 2020The American College of Cardiology decided to cancel ACC.20/WCC due to COVID-19, which was scheduled to take place March 28-30 in Chicago. However, ACC.20/WCC Virtual Meeting continues to release cutting edge science and practice changing updates for cardiovascular professionals on demand and free through June 2020.
- ASCO 2019The 2019 ASCO Annual Meeting, taking place May 31-June 4 in Chicago, will bring together more than 32,000 oncology professionals from across the globe. The theme of this year’s conference is Caring for Every Patient, Learning From Every Patient.