activity
20182023
most citedSkin Lesion Classification Using CNNs with Patch-Based Attention and Diagnosis-Guided Loss Weighting

180 citations · 630 across the 49 of their papers we have counts for

collaborators

56 papers

cs.CV2023

VR-based body tracking to stimulate musculoskeletal training

M. Neidhardt, S. Gerlach F. N. Schmidt, I. A. K. Fiedler +3

Training helps to maintain and improve sufficient muscle function, body control, and body coordination. These are important to reduce the risk of fracture incidents caused by falls…

cs.RO2023★ 1 cited

Collaborative Robotic Biopsy with Trajectory Guidance and Needle Tip Force Feedback

Robin Mieling, Maximilian Neidhardt, Sarah Latus +6

The diagnostic value of biopsies is highly dependent on the placement of needles. Robotic trajectory guidance has been shown to improve needle positioning, but feedback for real-ti…

eess.IV2023

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…

eess.IV2023

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…

eess.IV2023

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…

eess.IV2023★ 10 cited

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…