Publications

Research outputs

Selected publications in medical imaging and machine learning. Browse the broader record on Google Scholar.

16 selected outputs

Recent papers & preprints

CRIL-U-Net: Compact Ratio-Interaction Learning for Focal Cortical Dysplasia Segmentation from T1w and FLAIR MRI

Ghosh S, Mandal S, Goswami T, Arya AS, Phamnguyen J, Vashistha R. 2026.

Accepted at the International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD), Edinburgh, United Kingdom, 2026.

Preprint ↗

Recent papers & preprints

Benchmarking MRI Representations for Deep Learning-Based Focal Cortical Dysplasia Segmentation

Ghosh S, Phamnguyen J, Arya AS, Mandal S, Goswami T, Vashistha R. 2026.

Accepted at the 11th International Conference on Computer Vision and Image Processing (CVIP 2026), National Institute of Technology Calicut, Kozhikode, Kerala, India, 9–12 December 2026. Preprint available.

Read on arXiv ↗

Recent papers & preprints

NeuroMorphix: A Novel Brain MRI Asymmetry-specific Feature Construction Approach for Seizure Recurrence Prediction

Ghosh S, Vegh V, Moinian S, Moradi H, Sullivan AA, Phamnguyen J, Reutens D. 2024. Preprint.

Read on arXiv ↗

Journal articles

Image synthesis of interictal SPECT from MRI and PET using machine learning

Fard AS, Reutens DC, Ramsay SC, Goodman SJ, Ghosh S, Vegh V.

Frontiers in Neurology, 15:1383773, 2024.

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Journal articles

Automated extraction of the arterial input function from brain images for parametric PET studies

Moradi H, Vashistha R, Ghosh S, O’Brien K, Hammond A, Rominger A, Sari H, Shi K, Vegh V, Reutens DC.

EJNMMI Research, 14:33, 2024.

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Published conference papers

Stress-testing cross-cancer generalizability of 3D nnU-Net for PET-CT tumour segmentation: multi-cohort evaluation with novel oesophageal and lung cancer datasets

Ghosh S, Jestin Hannan C, Vashistha R, Kundu P, Brosda S, Aoude LG, Lonie J, Nathanson A, Ng J, Barbour AP, Vegh V.

International Conference on Computer Vision and Image Processing (CVIP), Indian Institute of Technology Ropar, Rupnagar, India, 2025. Published conference paper.

arXiv version ↗

Published conference papers

RCCNet: An Efficient Convolutional Neural Network for Histological Routine Colon Cancer Nuclei Classification

Basha SHS, Ghosh S, Babu KK, Dubey SR, Pulabaigari V, Mukherjee S. International Conference on Control, Automation, Robotics and Vision (ICARCV), Singapore, IEEE, 2018, pp. 1222–1227.

Publisher ↗

Published conference papers

Third Order Backward Elimination Approach for Fuzzy-Rough Set based Feature Selection

Ghosh S, Sai Prasad PSVS, Rao CR. International Conference on Pattern Recognition and Machine Intelligence (PReMI), Indian Statistical Institute, Kolkata, India, LNCS 10597, 2017, pp. 254–262.

Publisher ↗

Published conference papers

An Efficient Gaussian Kernel Based Fuzzy-Rough Set Approach for Feature Selection

Ghosh S, Sai Prasad PSVS, Rao CR. Multi-Disciplinary International Workshop on Artificial Intelligence (MIWAI), Chiang Mai, Thailand, 2016, pp. 38–49.

Publisher ↗

Conference Abstracts

Deep Learning-Based Segmentation of Cerebellar Peduncles Using Diffusion MRI

Soumen Ghosh, Susmita Saha, Diogo H Shiraishi, Thiago J Rezende, Ian Harding, TRACK-FA Neuroimaging Consortium.

2026 · International Society for Magnetic Resonance in Medicine (ISMRM) Annual Meeting & Exhibition · Cape Town, South Africa · Conference abstract.

ISMRM abstract record (full text requires access) ↗

Conference Abstracts

Evaluating Deep Learning for Cerebellar Peduncle Segmentation: Assessing TractSeg’s Performance

Soumen Ghosh, Susmita Saha, Thiago Rezende, Ian Harding.

2025 · Organization for Human Brain Mapping (OHBM) Annual Meeting · Brisbane, Australia · Conference abstract.

OHBM abstract book (pp. 426–428) ↗

Conference Abstracts

Unsupervised Learning for Lesion Detection on 7T Brain MRI in Patients with Focal Epilepsy

Soumen Ghosh, Viktor Vegh, John Phamnguyen, Shahrzad Moinian, David Reutens.

2024 · Organization for Human Brain Mapping (OHBM) Annual Meeting · Seoul, South Korea · Conference abstract.

Read abstract (PDF, p. 2241) ↗

Conference Abstracts

Seizure Recurrence Prediction from MRI and Clinical Information Using Novel Brain Features for Machine Learning

Soumen Ghosh, Viktor Vegh, Alice-Ann Sullivan, Shahrzad Moinian, John Phamnguyen, David Reutens.

2023 · American Epilepsy Society (AES) Annual Meeting · Orlando, United States · Conference abstract.

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Conference Abstracts

NeuroMorphix: a brain-specific feature construction approach for 3D brain MRI classification

Soumen Ghosh, Viktor Vegh, Shahrzad Moinian, Alice-Ann Sullivan, David Reutens.

2023 · International Society for Magnetic Resonance in Medicine, Australia and New Zealand Chapter (ISMRM ANZ) Annual Meeting, Brisbane, Australia · Conference abstract.

Google Scholar record ↗

Conference Abstracts

Machine Learning-based Approach for Seizure Recurrence Prediction from Brain MRI

Soumen Ghosh, Viktor Vegh, Shahrzad Moinian, John Phamnguyen, Alice-Ann Sullivan, David Reutens.

2023 · Epilepsy Society of Australia (ESA), 37th Annual Scientific Meeting, Auckland, New Zealand · Conference abstract.

Google Scholar record ↗

Conference Abstracts

Early EEG Increases the Rate of Detection of Epileptiform Abnormalities After First Seizure

Alice-Ann Sullivan, Rebecca Kerr, Xiaohua Chen, Fred Tremayne, Soumen Ghosh, David Reutens.

2022 · American Epilepsy Society (AES) Annual Meeting · Nashville, United States · Conference abstract.

Read abstract ↗