Sailesh Conjeti | DeepAI

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∙ 05/09/2022

A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling

Solving the inverse problem is the key step in evaluating the capacity o...

0 Ivan Ezhov, et al. ∙

∙ 10/09/2019

FastSurfer – A fast and accurate deep learning based neuroimaging pipeline

Traditional neuroimage analysis pipelines involve computationally intens...

31 Leonie Henschel, et al. ∙

∙ 04/03/2019

FatSegNet : A Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI

Purpose: Development of a fast and fully automated deep learning pipelin...

0 Santiago Estrada, et al. ∙

∙ 11/24/2018

Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation for Structure-wise Quality Control

We introduce Bayesian QuickNAT for the automated quality control of whol...

0 Abhijit Guha Roy, et al. ∙

∙ 10/11/2018

InfiNet: Fully Convolutional Networks for Infant Brain MRI Segmentation

We present a novel, parameter-efficient and practical fully convolutiona...

0 Shubham Kumar, et al. ∙

∙ 10/11/2018

Learning Optimal Deep Projection of ^18F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes

Several diseases of parkinsonian syndromes present similar symptoms at e...

0 Shubham Kumar, et al. ∙

∙ 07/30/2018

Human Motion Analysis with Deep Metric Learning

Effectively measuring the similarity between two human motions is necess...

0 Huseyin Coskun, et al. ∙

∙ 07/20/2018

Competition vs. Concatenation in Skip Connections of Fully Convolutional Networks

Increased information sharing through short and long-range skip connecti...

0 Santiago Estrada, et al. ∙

∙ 07/09/2018

Complex Fully Convolutional Neural Networks for MR Image Reconstruction

Undersampling the k-space data is widely adopted for acceleration of Mag...

18 Muneer Ahmad Dedmari, et al. ∙

∙ 06/29/2018

SynNet: Structure-Preserving Fully Convolutional Networks for Medical Image Synthesis

Cross modal image syntheses is gaining significant interests for its abi...

2 Deepa Gunashekar, et al. ∙

∙ 04/19/2018

Inherent Brain Segmentation Quality Control from Fully ConvNet Monte Carlo Sampling

We introduce inherent measures for effective quality control of brain se...

0 Abhijit Guha Roy, et al. ∙

∙ 03/31/2018

Webly Supervised Learning for Skin Lesion Classification

Within medical imaging, manual curation of sufficient well-labeled sampl...

0 Fernando Navarro, et al. ∙

∙ 03/23/2018

Generalizability vs. Robustness: Adversarial Examples for Medical Imaging

In this paper, for the first time, we propose an evaluation method for d...

0 Magdalini Paschali, et al. ∙

∙ 01/12/2018

QuickNAT: Segmenting MRI Neuroanatomy in 20 seconds

Whole brain segmentation from structural magnetic resonance imaging is a...

0 Abhijit Guha Roy, et al. ∙

∙ 05/02/2017

Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data

Training deep fully convolutional neural networks (F-CNNs) for semantic ...

0 Abhijit Guha Roy, et al. ∙

∙ 04/07/2017

ReLayNet: Retinal Layer and Fluid Segmentation of Macular Optical Coherence Tomography using Fully Convolutional Network

Optical coherence tomography (OCT) is used for non-invasive diagnosis of...

0 Abhijit Guha Roy, et al. ∙

∙ 03/16/2017

Learning Robust Hash Codes for Multiple Instance Image Retrieval

In this paper, for the first time, we introduce a multiple instance (MI)...

0 Sailesh Conjeti, et al. ∙

∙ 12/19/2016

Cross-Modal Manifold Learning for Cross-modal Retrieval

This paper presents a new scalable algorithm for cross-modal similarity ...

0 Sailesh Conjeti, et al. ∙

∙ 12/16/2016

Deep Residual Hashing

Hashing aims at generating highly compact similarity preserving code wor...

0 Sailesh Conjeti, et al. ∙

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