Abhijit Guha Roy

Abhijit Guha Roy

About me:
I am a PhD student, jointly affiliated with AI-Med at Ludwig Maximilian University and Department of Informatics at Technical University of Munich. The main focus of my research is to develop deep learning based solution for medical image analysis, with primary focus on Neuroimaging applications. Previously, I completed my masters at Indian Institute of Technology Kharagpur, India.

Email: abhijit.guha-roy[at]tum[dot]de / abhijit[at]ai-med[dot]de

My Profiles: Google Scholar / GitHub / LinkedIn

Research Focus: Bayesian Deep Learning, Fully Convolutional Networks, Computational Neuroimaging

 

 

Awards

  • MICCAI Student Travel Award 2018
  • MICCAI Young Investigator Award Runner Up 2017 (10 papers out of 950 submissions)
  • MICCAI Student Travel Award 2017
  • DAAD PhD Fellowship 2016

 

Publications:

Journals

  1. Guha Roy, A., Conjeti,S., Navab, N., Wachinger, C. (2018). QuickNAT: A Fully Convolutional Network for Quick and Accurate Segmentation of Neuroanatomy. NeuroImage. (Impact factor – 5.43)
  2. Guha Roy, A., Navab, N., Wachinger, C. (2018). Recalibrating Fully Convolutional Networks with Spatial and Channel ‘Squeeze & Excitation’Blocks. IEEE Transactions on Medical Imaging (Early Acess). (Impact factor – 6.13)
  3. Guha Roy, A., Conjeti, S., Karri, S.P.K., Sheet, D., Katouzian, A., Wachinger, C., Navab, N. (2017). ReLayNet: Retinal Layer and Fluid Segmentation of Macular Optical Coherence Tomography using Fully Convolutional Network. Biomed. Optics Express, 8(8), pp. 3627-3642, 2017. (Impact factor – 3.48)
  4. Conjeti, S., Katouzian, A., Guha Roy, A., Peter, L., Sheet, D., Carlier, S., Laine, A. and Navab, N. (2016). Supervised domain adaptation of decision forests: Transfer of models trained in vitro for in vivo intravascular ultrasound tissue characterization. Medical Image Analysis, 32, pp.1-17. (Impact factor – 5.35)
  5. Guha Roy, A., Conjeti, S., Carlier, S.G., Dutta, P.K., Kastrati, A., Laine, A.F., Navab, N., Katouzian, A. and Sheet, D. (2016). Lumen Segmentation in Intravascular Optical Coherence Tomography Using Backscattering Tracked and Initialized Random Walks. IEEE Journal of Biomedical and Health Informatics, 20(2), pp.606-614. (Impact factor – 3.85)

Conferences

  1. Guha Roy, A., Conjeti, S., Navab, N. and Wachinger, C. (2018). Inherent Brain Segmentation Quality Control from Fully ConvNet Monte Carlo Sampling. Accepted at Med. Image Comput., Comp. Assist. Interv. (MICCAI), 2018.
  2. Guha Roy, A., Navab, N. and Wachinger, C. (2018). Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks. Accepted at Med. Image Comput., Comp. Assist. Interv. (MICCAI), 2018. (Oral Presentation, Top 4% of submissions)
  3. Guha Roy, A., Conjeti, S., Sheet, D., Katouzian, A., Navab, N. and Wachinger, C. (2017). Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data. In Proc. Med. Image Comput., Comp. Assist. Interv. (MICCAI), 2017.
  4. Conjeti, S., Guha Roy, A., Katouzian, A., Navab, N. (2017). Hashing with Residual Networks for Image Retrieval. In Proc. Med. Image Comput., Comp. Assist. Interv. (MICCAI), 2017.
  5. Das, K., Karri, S.P.K., Guha Roy, A., Chatterjee, J. and Sheet, D. (2017). Classifying Histopathology Whole slides using Fusion of Decisions from Deep Convolutional Network on a Collection of Random Multi views at Multi magni cation. International Symposium on Biomedical Imaging (ISBI) pp. 1024-1027.
  6. Lahiri, A. , Guha Roy, A. , Sheet, D. and Biswas, P.K. (2016) Deep Neural Ensemble for Retinal Vessel Segmentation in Fundus Images towards Achieving Label-Free Angiography. International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). pp. 1340-1343.
  7. Guha Roy, A., Conjeti, S. , Carlier, S., Dutta, P., Kastrati, A., Laine, A. F., Navab, N., Katouzian, A. and Sheet, D. (2016). Multiscale Distribution Preserving Autoencoders for Susceptible Plaque Detection in Intravascular Optical Coherence Tomography. International Symposium on Biomedical Imaging (ISBI) pp. 1359- 1362.
  8. Guha Roy, A. and Sheet, D. (2015). DASA: Domain Adaptation in Stacked Autoencoders using Systematic Dropout. Asian Conference on Pattern Recognition (ACPR). pp. 735-739.
  9. Guha Roy, A., Conjeti, S., Carlier, S. G., Konig, A., Kastrati, A., Dutta, P. K., Laine, A.F., Navab, N., Sheet, D. and Katouzian, A. (2015). Bag of forests for modelling of tissue energy interaction in optical coherence tomography for atherosclerotic plaque susceptibility assessment. International Symposium onBiomedical Imaging (ISBI) pp. 428-431.