Kaustav Bera
Orcid: 0000-0002-0962-4368
According to our database1,
Kaustav Bera
authored at least 25 papers
between 2017 and 2022.
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Bibliography
2022
Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma.
IEEE Trans. Medical Imaging, 2022
Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers.
CoRR, 2022
2021
Integrated Clinical and CT Based Artificial Intelligence Nomogram for Predicting Severity and Need for Ventilator Support in COVID-19 Patients: A Multi-Site Study.
IEEE J. Biomed. Health Informatics, 2021
Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers.
Medical Image Anal., 2021
LuMiRa: An Integrated Lung Deformation Atlas and 3D-CNN Model of Infiltrates for COVID-19 Prognosis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
2020
Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study.
Frontiers Comput. Neurosci., 2020
Can tumor location on pre-treatment MRI predict likelihood of pseudo-progression versus tumor recurrence in Glioblastoma? A feasibility study.
CoRR, 2020
Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study.
CoRR, 2020
Texture kinetic features from pre-treatment DCE MRI for predicting pathologic tumor stage regression after neoadjuvant chemoradiation in rectal cancers.
Proceedings of the Medical Imaging 2020: Image-Guided Procedures, 2020
Texture features distinguish benign cell clusters from adenocarcinomas on bile duct brushing cytology images.
Proceedings of the Medical Imaging 2020: Digital Pathology, 2020
Computer extracted features related to the spatial arrangement of tumor-infiltrating lymphocytes predict overall survival in epithelial ovarian cancer receiving adjuvant chemotherapy.
Proceedings of the Medical Imaging 2020: Digital Pathology, 2020
Computationally derived cytological image markers for predicting risk of relapse in acute myeloid leukemia patients following bone marrow transplantation.
Proceedings of the Medical Imaging 2020: Digital Pathology, 2020
Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Multi-site evaluation of stable radiomic features for more accurate evaluation of pathologic downstaging on MRI after chemoradiation for rectal cancers.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
2019
Radiomic characterization of perirectal fat on MRI enables accurate assessment of tumor regression and lymph node metastasis in rectal cancers after chemoradiation.
Proceedings of the Medical Imaging 2019: Image-Guided Procedures, 2019
Integrating radiomic features from T2-weighted and contrast-enhanced MRI to evaluate pathologic rectal tumor regression after chemoradiation.
Proceedings of the Medical Imaging 2019: Image-Guided Procedures, 2019
Region-specific fully convolutional networks for segmentation of the rectal wall on post-chemoradiation T2w MRI.
Proceedings of the Medical Imaging 2019: Image-Guided Procedures, 2019
Proceedings of the Radiomics and Radiogenomics in Neuro-oncology, 2019
A combination of intra- and peritumoral features on baseline CT scans is associated with overall survival in non-small cell lung cancer patients treated with immune checkpoint inhibitors: a multi-agent multi-site study.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Quantitative vessel tortuosity radiomics on baseline non-contrast lung CT predict response to immunotherapy and are prognostic of overall survival.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
2018
Automated segmentation and radiomic characterization of visceral fat on bowel MRIs for Crohn's disease.
Proceedings of the Medical Imaging 2018: Image-Guided Procedures, 2018
RaPtomics: integrating radiomic and pathomic features for predicting recurrence in early stage lung cancer.
Proceedings of the Medical Imaging 2018: Digital Pathology, 2018
Feature Driven Local Cell Graph (FeDeG): Predicting Overall Survival in Early Stage Lung Cancer.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
2017