58 citations · 64 across the 5 of their papers we have counts for
5 papers
QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge
Hongwei Bran Li, Fernando Navarro, Ivan Ezhov +77
Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a sign…
Generative Adversarial Networks based Skin Lesion Segmentation
Shubham Innani, Prasad Dutande, Ujjwal Baid +5
Skin cancer is a serious condition that requires accurate diagnosis and treatment. One way to assist clinicians in this task is using computer-aided diagnosis (CAD) tools that auto…
Deep Learning based Novel Cascaded Approach for Skin Lesion Analysis
Shubham Innani, Prasad Dutande, Bhakti Baheti +2
Automatic lesion analysis is critical in skin cancer diagnosis and ensures effective treatment. The computer aided diagnosis of such skin cancer in dermoscopic images can significa…
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta, Angelos Filos, Ujjwal Baid +89
Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges.…
Colorectal Cancer Segmentation using Atrous Convolution and Residual Enhanced UNet
Nisarg A. Shah, Divij Gupta, Romil Lodaya +2
Colorectal cancer is a leading cause of death worldwide. However, early diagnosis dramatically increases the chances of survival, for which it is crucial to identify the tumor in t…