Debayan Bhattacharya

Debayan Bhattacharya

Debayan Bhattacharya

 

 

 

 

 

 

 Research Assistant

 +49 (0)40 42878 3547

  E.3087

 debayan.Bhattacharya(at)tuhh.de

2021 - today MTEC Institute / TUHH
2018 - 2021 TUHH ( M.Sc.)

Interests

Deep learning for medical image analysis

Roles

  • Research assistant
  • PhD student

Publications

2022

  • D. Bhattacharya, B. T. Becker, F. Behrendt, M. Bengs, D. Beyersdorff, D. Eggert, E. Petersen, F. Jansen, M. Petersen, B. Cheng, C. Betz, A. Schlaefer, A. S. Hoffmann (2022). Supervised Contrastive Learning to Classify Paranasal Anomalies in the Maxillary Sinus. In Wang, Linwei, Dou, Qi, Fletcher, P. Thomas, Speidel, Stefanie, Li, Shuo (Eds.) Medical Image Computing, Computer Assisted Intervention -- MICCAI 2022 Springer Nature Switzerland: Cham 429-438 [Abstract] [doi] [www] [BibTex]

  • D. Bhattacharya, D. Eggert, C. Betz, A. Schlaefer (2022). Squeeze, multi-context attention for polyp segmentation. International Journal of Imaging Systems, Technology.Accepted. [Abstract] [doi] [www] [BibTex]

  • D. Bhattacharya, F. Behrendt, A. Felicio-Briegel, V. Volgger, D. Eggert, C. Betz, A. Schlaefer (2022). Learning Robust Representation for Laryngeal Cancer Classification in Vocal Folds from Narrow Band Images. Medical Imaging with Deep Learning. Accepted [www] [BibTex]

  • F. Behrendt, M. Bengs, D. Bhattacharya, J. Krüger, R. Opfer, A. Schlaefer (2022). Capturing Inter-Slice Dependencies of 3D Brain MRI-Scans for Unsupervised Anomaly Detection. Medical Imaging with Deep Learning. Accepted [www] [BibTex]

2021

  • D. Bhattacharya, C. Betz, D. Eggert, A. Schlaefer (2021). Self-Supervised U-Net for Segmenting Flat and Sessile Polyps. SPIE Medical Imaging Symposium 2022 Accepted. [Abstract] [www] [BibTex]

  • D. Bhattacharya, C. Betz, D. Eggert, A. Schlaefer (2021). Dual Parallel Reverse Attention Edge Network : DPRA-EdgeNet. Nordic Machine Intelligence, MedAI2021. 1 (1), 11-13 Second place in challenge task. [Abstract] [doi] [BibTex]