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3D Slicer as an image computing platform for the Quantitative Imaging Network.
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
- Bjoern H Menze, A. Jakab, K. Leemput
- Computer ScienceIEEE Transactions on Medical Imaging
- 1 October 2015
The set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences are reported, finding that different algorithms worked best for different sub-regions, but that no single algorithm ranked in the top for all sub-Regions simultaneously.
The RSNA Pediatric Bone Age Machine Learning Challenge.
The RSNA Pediatric Bone Age Machine Learning Challenge showed how a coordinated approach to solving a medical imaging problem can be successfully conducted and will catalyze collaboration and development of ML tools and methods that can potentially improve diagnostic accuracy and patient care.
Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging
A deep learning technique is developed to noninvasively predict IDH genotype in grade II–IV glioma using conventional MR imaging using a multi-institutional data set.
Overview of the CLEF 2009 Medical Image Retrieval Track
- H. Müller, Jayashree Kalpathy-Cramer, W. Hersh
- Medicine, Computer ScienceConference and Labs of the Evaluation Forum
- 30 September 2009
2009 was the sixth year for the ImageCLEF medical retrieval task and for the first time, 5 case-based topics were provided as an exploratory task, designed to be closer to the clinical workflow.
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification
The RSNA-ASNR-MICCAI BraTS 2021 challenge targets the evaluation of computational algorithms assessing the same tumor compartmentalization, as well as the underlying tumor’s molecular characterization, in pre-operative baseline mpMRI data from 2,000 patients.
Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks
This fully automated algorithm diagnosed plus disease in ROP with comparable or better accuracy than human experts, which has potential applications in disease detection, monitoring, and prognosis in infants at risk of ROP.
Improved tumor oxygenation and survival in glioblastoma patients who show increased blood perfusion after cediranib and chemoradiation
- T. Batchelor, E. Gerstner, R. Jain
- Medicine, BiologyProceedings of the National Academy of Sciences
- 4 November 2013
It is demonstrated that improved perfusion occurs only in a subset of patients in cediranib-containing regimens, and is associated with improved overall survival in these nGBM patients, and these results may provide new insight into the selection of glioblastoma patients most likely to benefit from anti-VEGF treatments.
PROSTATEx Challenges for computerized classification of prostate lesions from multiparametric magnetic resonance images
This work presents a computerized classification of clinically significant prostate lesions and the computerized determination of Gleason Grade Group in prostate cancer, both based on multiparametric magnetic resonance images, and finds that superiority to random guessing can be established for only two methods.
Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials.
The current document outlines consensus recommendations for a standardized Brain Tumor Imaging Protocol (BTIP), along with the scientific and practical justifications for these recommendations, resulting from a series of discussions between various experts involved in aspects of neuro-oncology neuroimaging for clinical trials.