Abhishek Mahajan

Orcid: 0000-0001-6606-6537

According to our database1, Abhishek Mahajan authored at least 16 papers between 2017 and 2023.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

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

2021
A 2021 update on cancer image analytics with deep learning.
WIREs Data Mining Knowl. Discov., 2021

Automatic lung segmentation for the inclusion of juxtapleural nodules and pulmonary vessels using curvature based border correction.
J. King Saud Univ. Comput. Inf. Sci., 2021

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

2020
Deep Deconvolutional Residual Network Based Automatic Lung Nodule Segmentation.
J. Digit. Imaging, 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

2019
Radiomics for peripheral zone and intra-prostatic urethra segmentation in MR imaging.
Biomed. Signal Process. Control., 2019

Multicollinearity Analysis for Cuffless Blood Pressure Estimation Regression Algorithms.
Proceedings of the ICBSP 2019: 4th International Conference on Biomedical Imaging, 2019

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

Radiomics based detection and characterization of suspicious lesions on full field digital mammograms.
Comput. Methods Programs Biomed., 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
Nonsubsampled rotated complex wavelet transform (NSRCxWT) for medical image fusion related to clinical aspects in neurocysticercosis.
Comput. Biol. Medicine, 2017


  Loading...