9 papers · 1 filter
Leveraging Transfer Learning with Class-Specific Decoders for Laparoscopic Segmentation
Priya Tomar, Aditya Parikh, Christian Bauckhage +1
Effective multi-organ segmentation in surgical data requires learning the intricate anatomical features and alleviating the challenge of class imbalance, which results from relativ…
First Investigation of Deep Learning for Intraoperative Gauze Segmentation in Minimally Invasive Abdominal Surgery
Priya Tomar, Maximilian BroÃ, Philipp Feodorovici +7
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 se…
Hybrid Deep Learning for Traceability and Classification of Industrial Slate Tiles
Soren Antebi, Stefan Eickeler, Sandra Halscheidt +4
Applying deep learning to instance-aware reidentification of slate tiles and extraction site classification can improve production efficiency and quality control in the slate tile…
Knowing When Not to Predict: Self Supervised Learning and Abstention for Safer DR Screening
Muskaan Chopra, Lorenz Sparrenberg, Jan H. Terheyden +1
Self-supervised learning (SSL) is now a standard way to pretrain medical image models, but performance is still mostly judged by downstream accuracy. For safety-critical screening…
Generalizing Abstention for Noise-Robust Learning in Medical Image Segmentation
Wesam Moustafa, Hossam Elsafty, Helen Schneider +2
Label noise is a critical problem in medical image segmentation, often arising from the inherent difficulty of manual annotation. Models trained on noisy data are prone to overfitt…
From Retinal Pixels to Patients: Evolution of Deep Learning Research in Diabetic Retinopathy Screening
Muskaan Chopra, Lorenz Sparrenberg, Armin Berger +3
Diabetic Retinopathy (DR) remains a leading cause of preventable blindness, with early detection critical for reducing vision loss worldwide. Over the past decade, deep learning ha…