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most citedMonte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification

283 citations · 284 across the 3 of their papers we have counts for

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cs.CV2018283 cited

Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification

Marc Combalia, Veronica Vilaplana

We propose a patch sampling strategy based on a sequential Monte-Carlo method for high resolution image classification in the context of Multiple Instance Learning. When compared w…

cs.CV2018

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

Abhijit Guha Roy, Sailesh Conjeti, Nassir Navab +1

We introduce Bayesian QuickNAT for the automated quality control of whole-brain segmentation on MRI T1 scans. Next to the Bayesian fully convolutional neural network, we also prese…

cs.CV2018

InfiNet: Fully Convolutional Networks for Infant Brain MRI Segmentation

Shubham Kumar, Sailesh Conjeti, Abhijit Guha Roy +2

We present a novel, parameter-efficient and practical fully convolutional neural network architecture, termed InfiNet, aimed at voxel-wise semantic segmentation of infant brain MRI…

cs.CV2018

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

Shubham Kumar, Abhijit Guha Roy, Ping Wu +10

Several diseases of parkinsonian syndromes present similar symptoms at early stage and no objective widely used diagnostic methods have been approved until now. Positron emission t…

cs.CV2018

Human Motion Analysis with Deep Metric Learning

Huseyin Coskun, David Joseph Tan, Sailesh Conjeti +2

Effectively measuring the similarity between two human motions is necessary for several computer vision tasks such as gait analysis, person identi- fication and action retrieval. N…

cs.CV2018

Complex Fully Convolutional Neural Networks for MR Image Reconstruction

Muneer Ahmad Dedmari, Sailesh Conjeti, Santiago Estrada +3

Undersampling the k-space data is widely adopted for acceleration of Magnetic Resonance Imaging (MRI). Current deep learning based approaches for supervised learning of MRI image r…