1 code implementation • 29 Apr 2024 • Debayan Bhattacharya, Finn Behrendt, Benjamin Tobias Becker, Lennart Maack, Dirk Beyersdorff, Elina Petersen, Marvin Petersen, Bastian Cheng, Dennis Eggert, Christian Betz, Anna Sophie Hoffmann, Alexander Schlaefer
Lastly, we fine-tune the encoder part of the 3D CNN on a labelled dataset of normal and anomalous MS images.
no code implementations • 26 Apr 2023 • Debayan Bhattacharya, Sarah Latus, Finn Behrendt, Florin Thimm, Dennis Eggert, Christian Betz, Alexander Schlaefer
Needle positioning is essential for various medical applications such as epidural anaesthesia.
no code implementations • 31 Mar 2023 • Debayan Bhattacharya, Finn Behrendt, Benjamin Tobias Becker, Dirk Beyersdorff, Elina Petersen, Marvin Petersen, Bastian Cheng, Dennis Eggert, Christian Betz, Anna Sophie Hoffmann, Alexander Schlaefer
We demonstrate the feasibility of classifying anomalies in the MS. We propose a data enlarging strategy alongside a novel ensembling strategy that proves to be beneficial for paranasal anomaly classification in the MS.
no code implementations • 1 Nov 2022 • Debayan Bhattacharya, Finn Behrendt, Benjamin Tobias Becker, Dirk Beyersdorff, Elina Petersen, Marvin Petersen, Bastian Cheng, Dennis Eggert, Christian Betz, Anna Sophie Hoffmann, Alexander Schlaefer
However, experienced clinicians can segregate between normal samples (healthy maxillary sinus) and anomalous samples (anomalous maxillary sinus) after looking at a few normal samples.
no code implementations • 5 Sep 2022 • Debayan Bhattacharya, Benjamin Tobias Becker, Finn Behrendt, Marcel Bengs, Dirk Beyersdorff, Dennis Eggert, Elina Petersen, Florian Jansen, Marvin Petersen, Bastian Cheng, Christian Betz, Alexander Schlaefer, Anna Sophie Hoffmann
Particularly, we use a supervised contrastive loss that encourages embeddings of maxillary sinus volumes with and without anomaly to form two distinct clusters while the cross-entropy loss encourages the 3D CNN to maintain its discriminative ability.
no code implementations • 17 Oct 2021 • Debayan Bhattacharya, Christian Betz, Dennis Eggert, Alexander Schlaefer
This is followed by a supervised training on the limited Kvasir-Sessile dataset.
no code implementations • 2 Jul 2020 • Marcel Bengs, Nils Gessert, Wiebke Laffers, Dennis Eggert, Stephan Westermann, Nina A. Mueller, Andreas O. H. Gerstner, Christian Betz, Alexander Schlaefer
We analyze the value of using multiple hyperspectral bands compared to conventional RGB images and we study several machine learning models' ability to make use of the additional spectral information.
no code implementations • 21 Apr 2020 • Marcel Bengs, Stephan Westermann, Nils Gessert, Dennis Eggert, Andreas O. H. Gerstner, Nina A. Mueller, Christian Betz, Wiebke Laffers, Alexander Schlaefer
A recent study has shown that hyperspectral imaging (HSI) can be used for non-invasive detection of head and neck tumors, as precancerous or cancerous lesions show specific spectral signatures that distinguish them from healthy tissue.