21 citations · 43 across the 10 of their papers we have counts for
5 papers · 1 filter
Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs
Finn Behrendt, Debayan Bhattacharya, Robin Mieling +4
The application of supervised models to clinical screening tasks is challenging due to the need for annotated data for each considered pathology. Unsupervised Anomaly Detection (UA…
Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges
Debesh Jha, Vanshali Sharma, Debapriya Banik +30
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps durin…
Tissue Classification During Needle Insertion Using Self-Supervised Contrastive Learning and Optical Coherence Tomography
Debayan Bhattacharya, Sarah Latus, Finn Behrendt +4
Needle positioning is essential for various medical applications such as epidural anaesthesia. Physicians rely on their instincts while navigating the needle in epidural spaces. Th…
Multiple Instance Ensembling For Paranasal Anomaly Classification In The Maxillary Sinus
Debayan Bhattacharya, Finn Behrendt, Benjamin Tobias Becker +8
Paranasal anomalies are commonly discovered during routine radiological screenings and can present with a wide range of morphological features. This diversity can make it difficult…
Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI
Finn Behrendt, Debayan Bhattacharya, Julia Krüger +2
The use of supervised deep learning techniques to detect pathologies in brain MRI scans can be challenging due to the diversity of brain anatomy and the need for annotated data set…