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Aditya Parikh

3 papers indexed

arxivcs.CVcs.LG2026-07-31

Leveraging Transfer Learning with Class-Specific Decoders for Laparoscopic Segmentation

Priya Tomar, Aditya Parikh, Christian Bauckhage, Rafet Sifa

Effective multi-organ segmentation in surgical data requires learning the intricate anatomical features and alleviating the challenge of class imbalance, which results from relatively lower proportions of small and limitedly exposed structures. Recent works on laparoscopic multi-…

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arxivcs.CV2026-07-31

First Investigation of Deep Learning for Intraoperative Gauze Segmentation in Minimally Invasive Abdominal Surgery

Priya Tomar, Maximilian Broß, Philipp Feodorovici, Jan Arensmeyer, Philipp Leifels, Aditya Parikh, et al.

Surgical gauze is an essential part of surgical procedures, primarily used for controlling bleeding and absorbing bodily fluids. The post-surgical retention of gauze can lead to serious complications and necessitate additional surgery for its removal. Despite the clinical signifi…

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arxiveess.IVcs.CVcs.CYcs.LG2026-07-08

False Confidence: Automated Labels Confound Fairness Audits in Cervical Spine Segmentation

Linus Juni, Aasa Feragen, Aditya Parikh

Automated segmentation of cervical-spine MRI is increasingly used in clinical workflows, yet no fairness audit exists for this anatomy. We show that auditing these segmentation tasks is complicated by a common property of modern segmentation datasets: expert-annotated gold labels…

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