Ujjwal Baid

According to our database1, Ujjwal Baid authored at least 36 papers between 2017 and 2023.

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Bibliography

2023
Federated benchmarking of medical artificial intelligence with MedPerf.
Nat. Mac. Intell., July, 2023

The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa).
CoRR, 2023

Generative Adversarial Networks based Skin Lesion Segmentation.
CoRR, 2023

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs).
CoRR, 2023

The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn).
CoRR, 2023

The Brain Tumor Segmentation (BraTS) Challenge 2023: Local Synthesis of Healthy Brain Tissue via Inpainting.
CoRR, 2023

The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma.
CoRR, 2023

Why is the winner the best?
CoRR, 2023

Why is the Winner the Best?
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
ADAM Challenge: Detecting Age-Related Macular Degeneration From Fundus Images.
IEEE Trans. Medical Imaging, 2022

Biomedical image analysis competitions: The state of current participation practice.
CoRR, 2022

Federated Learning Enables Big Data for Rare Cancer Boundary Detection.
CoRR, 2022

Federated Learning for the Classification of Tumor Infiltrating Lymphocytes.
CoRR, 2022

REFUGE2 Challenge: Treasure for Multi-Domain Learning in Glaucoma Assessment.
CoRR, 2022

ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images.
CoRR, 2022

Deep Residual Separable Convolutional Neural Network for lung tumor segmentation.
Comput. Biol. Medicine, 2022

Deep Learning Based Novel Cascaded Approach for Skin Lesion Analysis.
Proceedings of the Computer Vision and Image Processing - 7th International Conference, 2022

2021
MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge.
IEEE Trans. Medical Imaging, 2021

Cascaded Dilated Deep Residual Network for Volumetric Liver Segmentation From CT Image.
Int. J. E Health Medical Commun., 2021

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results.
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CoRR, 2021

The University of California San Francisco Preoperative Diffuse Glioma (UCSF-PDGM) MRI Dataset.
CoRR, 2021

The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification.
CoRR, 2021

The Federated Tumor Segmentation (FeTS) Challenge.
CoRR, 2021

GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging.
CoRR, 2021

LNCDS: A 2D-3D cascaded CNN approach for lung nodule classification, detection and segmentation.
Biomed. Signal Process. Control., 2021

Detecting Covid-19 and Community Acquired Pneumonia Using Chest CT Scan Images With Deep Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021

Fuse-PN: A Novel Architecture for Anomaly Pattern Segmentation in Aerial Agricultural Images.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
A Novel Approach for Fully Automatic Intra-Tumor Segmentation With 3D U-Net Architecture for Gliomas.
Frontiers Comput. Neurosci., 2020

Overall Survival Prediction in Glioblastoma With Radiomic Features Using Machine Learning.
Frontiers Comput. Neurosci., 2020


Colorectal Cancer Segmentation Using Atrous Convolution and Residual Enhanced UNet.
Proceedings of the Computer Vision and Image Processing - 5th International Conference, 2020

2019
Detection of Pathological Myopia and Optic Disc Segmentation with Deep Convolutional Neural Networks.
Proceedings of the TENCON 2019, 2019

Brain Tumor Segmentation with Cascaded Deep Convolutional Neural Network.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.
CoRR, 2018

Deep Learning Radiomics Algorithm for Gliomas (DRAG) Model: A Novel Approach Using 3D UNET Based Deep Convolutional Neural Network for Predicting Survival in Gliomas.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018

2017
Brain Tumor Segmentation Based on Non Negative Matrix Factorization and Fuzzy Clustering.
Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017), 2017


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