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Kernel of CycleGAN as a Principle homogeneous space
Unpaired image-to-image translation has attracted significant interest d...
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Contextual Two-Stage U-Nets for Robust Pulmonary Lobe Segmentation in CT Scans of COVID-19 and COPD Patients
Pulmonary lobe segmentation in computed tomography scans is essential fo...
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Neural Image Compression for Gigapixel Histopathology Image Analysis
We present Neural Image Compression (NIC), a method to reduce the size o...
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Streaming convolutional neural networks for end-to-end learning with multi-megapixel images
Due to memory constraints on current hardware, most convolution neural n...
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Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images
Automated classification of histopathological whole-slide images (WSI) o...
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Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation
Magnetic Resonance Imaging (MRI) is widely used in routine clinical diag...
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Deep Multi-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin
Lacunes of presumed vascular origin (lacunes) are associated with an inc...
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Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities
The anatomical location of imaging features is of crucial importance for...
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Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR
Ventricular volume and its progression are known to be linked to several...
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Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network
Computer-aided detection or decision support systems aim to improve brea...
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Training convolutional neural networks with megapixel images
To train deep convolutional neural networks, the input data and the inte...
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Unsupervised Prostate Cancer Detection on H&E using Convolutional Adversarial Autoencoders
We propose an unsupervised method using self-clustering convolutional ad...
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Detecting SNPs with interactive effects on a quantitative trait
Here we propose a test to detect effects of single nucleotide polymorphi...
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Deep Learning Framework for Digital Breast Tomosynthesis Reconstruction
Digital breast tomosynthesis is rapidly replacing digital mammography as...
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Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation
Computer-aided detection aims to improve breast cancer screening program...
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Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks
Manual counting of mitotic tumor cells in tissue sections constitutes on...
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Chest X-ray Inpainting with Deep Generative Models
Generative adversarial networks have been successfully applied to inpain...
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GANs for Medical Image Analysis
Generative Adversarial Networks (GANs) and their extensions have carved ...
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Comparison of U-net-based Convolutional Neural Networks for Liver Segmentation in CT
Various approaches for liver segmentation in CT have been proposed: Besi...
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Chest X-Rays Image Inpainting with Context Encoders
Chest X-rays are one of the most commonly used technologies for medical ...
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Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology
Stain variation is a phenomenon observed when distinct pathology laborat...
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Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification
Large amounts of unlabelled data are commonplace for many applications i...
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FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis
In this work, we propose a method to reject out-of-distribution samples ...
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A powerful MAF-neutral allele-based test for case-control association studies
In a case-control study aimed at locating autosomal disease variants for...
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Random smooth gray value transformations for cross modality learning with gray value invariant networks
Random transformations are commonly used for augmentation of the trainin...
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Extending Unsupervised Neural Image Compression With Supervised Multitask Learning
We focus on the problem of training convolutional neural networks on gig...
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Inferring astrophysical X-ray polarization with deep learning
We investigate the use of deep learning in the context of X-ray polariza...
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Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels
Prostate cancer is the most prevalent cancer among men in Western countr...
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Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation
The two-dimensional nature of mammography makes estimation of the overal...
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Deep Learning with robustness to missing data: A novel approach to the detection of COVID-19
In the context of the current global pandemic and the limitations of the...
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