Author

H. Veeraraghavan

3 papers indexed here

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Open access Oct 2026

External evaluation of a deep learning-based algorithm for automated lung tumor and esophagus segmentation on CBCT.

Online adaptive radiotherapy (ART) requires fast and accurate delineation of targets and organs at risk on cone-beam computed tomography (CBCT). Although deep learning (DL)-based CBCT auto-segmentation methods have been proposed, their clinical generalizability remains insufficiently validated. This study aimed to exte...

Zhe-Hao Zhang, D. Hobbis, Jue Jiang et al. · Biomedical engineering and p... · 0 citations

Open access Aug 2026

Deep Learning Enables Automated Detection of Mature B Cell Neoplasms by Flow Cytometry.

Multiparameter flow cytometry is essential for diagnosing mature B-cell lymphomas, yet analysis remains largely manual, time-consuming, and subject to inter-operator variability. We developed an automated system for B-cell neoplasm detection using a three-stage deep learning architecture that produces interpretable int...

S. Chalise, Mikhail Roshal, Qi Gao et al. · Modern Pathology · 0 citations

Preprint Aug 2026

Parameter-Efficient pretrained-CT-to-MRI Transfer for Rectal Cancer Segmentation: Performance-Calibration Trade-offs

SWIFT, a SWin pretrained model wtih parameter-eFficient and tumor-aware fine-tuning for rectal cancer segmentation, is introduced, supporting robustness across pretrained initializations rather than external clinical generalizability.

A. Rangnekar, J. T. Gomez, J. Deasy et al. · 0 citations