An approach for real-time stress-trend detection using physiological signals in wearable computing systems for automotive drivers. - Rajiv Ranjan Singh; Sailesh Conjeti; Rahul Banerjee (ITSC, 2011)

Patient identification using high-confidence wavelet based Iris Pattern recognition. - Sailesh Conjeti; Dhiraj Puroshottam Jetwani (BHI, 2012)

Bio-inspired wearable computing architecture and physiological signal processing for on-road stress monitoring. - Sailesh Conjeti; Rajiv Ranjan Singh; Rahul Banerjee (BHI, 2012)

Detection of retinal vessels in fundus images through transfer learning of tissue specific photon interaction statistical physics. - Debdoot Sheet; Sri Phani Krishna Karri; Sailesh Conjeti; Sambuddha Ghosh; Jyotirmoy Chatterjee; Ajoy Kumar Ray (ISBI, 2013)

A comparative evaluation of neural network classifiers for stress level analysis of automotive drivers using physiological signals. - Rajiv Ranjan Singh; Sailesh Conjeti; Rahul Banerjee (Biomed. Signal Process. Control., 2013)

Full-Wave Intravascular Ultrasound Simulation from Histology. - Silvan Kraft; Sailesh Conjeti; Peter B. Noël; Stéphane G. Carlier; Nassir Navab; Amin Katouzian (MICCAI (2), 2014)

Shading Correction for Whole Slide Image Using Low Rank and Sparse Decomposition. - Tingying Peng; Lichao Wang; Christine Bayer; Sailesh Conjeti; Maximilian Baust; Nassir Navab (MICCAI (1), 2014)

Corrigendum to "A comparative evaluation of neural network classifiers for stress level analysis of automotive drivers using physiological signals" [Biomed. Signal Process. Control 8 (2013) 740-754]. - Rajiv Ranjan Singh; Sailesh Conjeti; Rahul Banerjee (Biomed. Signal Process. Control., 2014)

Assessment of Driver Stress from Physiological Signals collected under Real-Time Semi-Urban Driving Scenarios. - Rajiv Ranjan Singh; Sailesh Conjeti; Rahul Banerjee (Int. J. Comput. Intell. Syst., 2014)

Multi-scale Graph-based Guided Filter for De-noising Cryo-Electron Tomographic Data. - Shadi Albarqouni; Maximilian Baust; Sailesh Conjeti; Asharf Al-Amoudi; Nassir Navab (BMVC, 2015)

Deformable registration of immunofluorescence and histology using iterative cross-modal propagation. - Sailesh Conjeti; Mehmet Yigitsoy; Tingying Peng; Debdoot Sheet; Jyotirmoy Chatterjee; Christine Bayer; Nassir Navab; Amin Katouzian (ISBI, 2015)

Mutually coherent structural representation for image registration through joint manifold embedding and alignment. - Sailesh Conjeti; Mehmet Yigitsoy; Debdoot Sheet; Jyotirmoy Chatterjee; Nassir Navab; Amin Katouzian (ISBI, 2015)

Bag of forests for modelling of tissue energy interaction in optical coherence tomography for atherosclerotic plaque susceptibility assessment. - Abhijit Guha Roy; Sailesh Conjeti; Stephane G. Carlier; Andreas König 005; Adnan Kastrati; Pranab Kumar Dutta; Andrew F. Laine; Nassir Navab; Debdoot Sheet; Amin Katouzian (ISBI, 2015)

Hashing Forests for Morphological Search and Retrieval in Neuroscientific Image Databases. - Sepideh Mesbah; Sailesh Conjeti; Ajayrama Kumaraswamy; Philipp L. Rautenberg; Nassir Navab; Amin Katouzian (MICCAI (2), 2015)

Maximum inner product search for morphological retrieval of large-scale neuron data. - Zhongyu Li 002; Fumin Shen; Ruogu Fang; Sailesh Conjeti; Amin Katouzian; Shaoting Zhang 001 (ISBI, 2016)

Multiscale distribution preserving autoencoders for plaque detection in intravascular optical coherence tomography. - Abhijit Guha Roy; Sailesh Conjeti; Stephane G. Carlier; Khalil Houissa; Andreas König 005; Pranab K. Dutta; Andrew F. Laine; Nassir Navab; Amin Katouzian; Debdoot Sheet (ISBI, 2016)

Deeply learnt hashing forests for content based image retrieval in prostate MR images. - Amit Shah; Sailesh Conjeti; Nassir Navab; Amin Katouzian (Image Processing, 2016)

Survival analysis for high-dimensional, heterogeneous medical data: Exploring feature extraction as an alternative to feature selection. - Sebastian Pölsterl; Sailesh Conjeti; Nassir Navab; Amin Katouzian (Artif. Intell. Medicine, 2016)

Cross-Modal Manifold Learning for Cross-modal Retrieval. - Sailesh Conjeti; Anees Kazi; Nassir Navab; Amin Katouzian (CoRR, 2016)

Deep Residual Hashing. - Sailesh Conjeti; Abhijit Guha Roy; Amin Katouzian; Nassir Navab (CoRR, 2016)

Metric hashing forests. - Sailesh Conjeti; Amin Katouzian; Anees Kazi; Sepideh Mesbah; David Beymer; Tanveer F. Syeda-Mahmood; Nassir Navab (Medical Image Anal., 2016)

Supervised domain adaptation of decision forests: Transfer of models trained in vitro for in vivo intravascular ultrasound tissue characterization. - Sailesh Conjeti; Amin Katouzian; Abhijit Guha Roy; Loïc Peter; Debdoot Sheet; Stéphane G. Carlier; Andrew Laine; Nassir Navab (Medical Image Anal., 2016)

Neuron-Miner: An Advanced Tool for Morphological Search and Retrieval in Neuroscientific Image Databases. - Sailesh Conjeti; Sepideh Mesbah; Mohammadreza Negahdar; Philipp L. Rautenberg; Shaoting Zhang 001; Nassir Navab; Amin Katouzian (Neuroinformatics, 2016)

Lumen Segmentation in Intravascular Optical Coherence Tomography Using Backscattering Tracked and Initialized Random Walks. - Abhijit Guha Roy; Sailesh Conjeti; Stephane G. Carlier; Pranab Kumar Dutta; Adnan Kastrati; Andrew F. Laine; Nassir Navab; Amin Katouzian; Debdoot Sheet (IEEE J. Biomed. Health Informatics, 2016)

Coupled Manifold Learning for Retrieval Across Modalities. - Anees Kazi; Sailesh Conjeti; Amin Katouzian; Nassir Navab (ICCV Workshops, 2017)

Deep Multiple Instance Hashing for Scalable Medical Image Retrieval. - Sailesh Conjeti; Magdalini Paschali; Amin Katouzian; Nassir Navab (MICCAI (3), 2017)

Hashing with Residual Networks for Image Retrieval. - Sailesh Conjeti; Abhijit Guha Roy; Amin Katouzian; Nassir Navab (MICCAI (3), 2017)

Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data. - Abhijit Guha Roy; Sailesh Conjeti; Debdoot Sheet; Amin Katouzian; Nassir Navab; Christian Wachinger (MICCAI (3), 2017)

Learning Robust Hash Codes for Multiple Instance Image Retrieval. - Sailesh Conjeti; Magdalini Paschali; Amin Katouzian; Nassir Navab (CoRR, 2017)

ReLayNet: Retinal Layer and Fluid Segmentation of Macular Optical Coherence Tomography using Fully Convolutional Network. - Abhijit Guha Roy; Sailesh Conjeti; Sri Phani Krishna Karri; Debdoot Sheet; Amin Katouzian; Christian Wachinger; Nassir Navab (CoRR, 2017)

Abstract: Deep Hashing for Large-Scale Medical Image Retrieval. - Sailesh Conjeti; Magdalini Paschali; Abhijit Guha Roy; Nassir Navab (Bildverarbeitung für die Medizin, 2018)

Abstract: Fast MRI Whole Brain Segmentation with Fully Convolutional Neural Networks. - Abhijit Guha Roy; Sailesh Conjeti; Nassir Navab; Christian Wachinger (Bildverarbeitung für die Medizin, 2018)

Human Motion Analysis with Deep Metric Learning. - Huseyin Coskun; David Joseph Tan; Sailesh Conjeti; Nassir Navab; Federico Tombari (ECCV (14), 2018)

Multiple instance learning of deep convolutional neural networks for breast histopathology whole slide classification. - Kausik Das; Sailesh Conjeti; Abhijit Guha Roy; Jyotirmoy Chatterjee; Debdoot Sheet (ISBI, 2018)

InfiNet: Fully convolutional networks for infant brain MRI segmentation. - Shubham Kumar; Sailesh Conjeti; Abhijit Guha Roy; Christian Wachinger; Nassir Navab (ISBI, 2018)

Complex Fully Convolutional Neural Networks for MR Image Reconstruction. - Muneer Ahmad Dedmari; Sailesh Conjeti; Santiago Estrada; Phillip Ehses; Tony Stöcker; Martin Reuter 001 (MLMIR@MICCAI, 2018)

Competition vs. Concatenation in Skip Connections of Fully Convolutional Networks. - Santiago Estrada; Sailesh Conjeti; Muneer Ahmad Dedmari; Nassir Navab; Martin Reuter 001 (MLMI@MICCAI, 2018)

Hashing-Based Atlas Ranking and Selection for Multiple-Atlas Segmentation. - Amin Katouzian; Hongzhi Wang 002; Sailesh Conjeti; Hui Tang; Ehsan Dehghan; Alexandros Karargyris; Anup Pillai; Kenneth L. Clarkson; Nassir Navab (MICCAI (4), 2018)

Learning Optimal Deep Projection of 18F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes. - Shubham Kumar; Abhijit Guha Roy; Ping Wu 003; Sailesh Conjeti; R. S. Anand; Jian Wang 009; Igor Yakushev; Stefan Förster; Markus Schwaiger; Sung-Cheng Huang; Axel Rominger; Chuantao Zuo; et al. (DLMIA/ML-CDS@MICCAI, 2018)

Webly Supervised Learning for Skin Lesion Classification. - Fernando Navarro; Sailesh Conjeti; Federico Tombari; Nassir Navab (MICCAI (2), 2018)

Generalizability vs. Robustness: Investigating Medical Imaging Networks Using Adversarial Examples. - Magdalini Paschali; Sailesh Conjeti; Fernando Navarro; Nassir Navab (MICCAI (1), 2018)

Inherent Brain Segmentation Quality Control from Fully ConvNet Monte Carlo Sampling. - Abhijit Guha Roy; Sailesh Conjeti; Nassir Navab; Christian Wachinger (MICCAI (1), 2018)

QuickNAT: Segmenting MRI Neuroanatomy in 20 seconds. - Abhijit Guha Roy; Sailesh Conjeti; Nassir Navab; Christian Wachinger (CoRR, 2018)

Generalizability vs. Robustness: Adversarial Examples for Medical Imaging. - Magdalini Paschali; Sailesh Conjeti; Fernando Navarro; Nassir Navab (CoRR, 2018)

SynNet: Structure-Preserving Fully Convolutional Networks for Medical Image Synthesis. - Deepa Gunashekar; Sailesh Conjeti; Abhijit Guha Roy; Nassir Navab; Kuangyu Shi (CoRR, 2018)

Learning to Hash for Large-Scale Medical Image Retrieval. - Sailesh Conjeti (2018)

Abstract: Leveraging Web Data for Skin Lesion Classification. - Fernando Navarro; Sailesh Conjeti; Federico Tombari; Nassir Navab (Bildverarbeitung für die Medizin, 2019)

Abstract: Adversarial Examples as Benchmark for Medical Imaging Neural Networks. - Magdalini Paschali; Sailesh Conjeti; Fernando Navarro; Nassir Navab (Bildverarbeitung für die Medizin, 2019)

Deep Learning for Volumetric Segmentation in Spatio-Temporal Data: Application to Segmentation of Prostate in DCE-MRI. - Jian Kang; Gihan Samarasinghe; Upul Senanayake; Sailesh Conjeti; Arcot Sowmya (ISBI, 2019)

FatSegNet : A Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI. - Santiago Estrada; Ran Lu; Sailesh Conjeti; Ximena Orozco-Ruiz; Joana Panos-Willuhn; Monique M. B. Breteler; Martin Reuter 001 (CoRR, 2019)

Bayesian QuickNAT: Model uncertainty in deep whole-brain segmentation for structure-wise quality control. - Abhijit Guha Roy; Sailesh Conjeti; Nassir Navab; Christian Wachinger (NeuroImage, 2019)

QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy. - Abhijit Guha Roy; Sailesh Conjeti; Nassir Navab; Christian Wachinger; Alzheimer's Disease Neuroimaging Initiative (NeuroImage, 2019)

Abstract: Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI. - Santiago Estrada; Ran Lu; Sailesh Conjeti; Ximena Orozco; Joana Panos; Monique M. B. Breteler; Martin Reuter 001 (Bildverarbeitung für die Medizin, 2020)

Abstract: FastSurfer. - Leonie Henschel; Sailesh Conjeti; Santiago Estrada; Kersten Diers; Bruce Fischl; Martin Reuter 001 (Bildverarbeitung für die Medizin, 2020)

Detection of Breast Cancer From Whole Slide Histopathological Images Using Deep Multiple Instance CNN. - Kausik Das; Sailesh Conjeti; Jyotirmoy Chatterjee; Debdoot Sheet (IEEE Access, 2020)

FastSurfer - A fast and accurate deep learning based neuroimaging pipeline. - Leonie Henschel; Sailesh Conjeti; Santiago Estrada; Kersten Diers; Bruce Fischl; Martin Reuter 001 (NeuroImage, 2020)

A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling. - Ivan Ezhov; Marcel Rosier; Lucas Zimmer; Florian Kofler; Suprosanna Shit; Johannes C. Paetzold; Kevin Scibilia; Felix Steinbauer; Leon Mächler; Katharina Franitza; Tamaz Amiranashvili; Martin J. Menten; et al. (ML4H@NeurIPS, 2022)

Casting the inverse problem as a database query. The case of personalized tumor growth modeling. - Ivan Ezhov; Marcel Rosier; Lucas Zimmer; Florian Kofler; Suprosanna Shit; Johannes C. Paetzold; Kevin Scibilia; Leon Mächler; Katharina Franitza; Tamaz Amiranashvili; Marie Metz; Sailesh Conjeti; et al. (CoRR, 2022)