
-
Coronary Artery Plaque Characterization from CCTA Scans using Deep Learning and Radiomics
Assessing coronary artery plaque segments in coronary CT angiography sca...
read it
-
ICDAR 2019 Competition on Image Retrieval for Historical Handwritten Documents
This competition investigates the performance of large-scale retrieval o...
read it
-
Epoch-wise label attacks for robustness against label noise
The current accessibility to large medical datasets for training convolu...
read it
-
Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-beam CT
Analyzing knee cartilage thickness and strain under load can help to fur...
read it
-
Fooling the Crowd with Deep Learning-based Methods
Modern, state-of-the-art deep learning approaches yield human like perfo...
read it
-
Deep autofocus with cone-beam CT consistency constraint
High quality reconstruction with interventional C-arm cone-beam computed...
read it
-
Learning New Tricks from Old Dogs – Inter-Species, Inter-Tissue Domain Adaptation for Mitotic Figure Assessment
For histopathological tumor assessment, the count of mitotic figures per...
read it
-
Projection-to-Projection Translation for Hybrid X-ray and Magnetic Resonance Imaging
Hybrid X-ray and magnetic resonance (MR) imaging promises large potentia...
read it
-
Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing
Deep learning-based image processing is capable of creating highly appea...
read it
-
Merging-ISP: Multi-Exposure High Dynamic Range Image Signal Processing
The image signal processing pipeline (ISP) is a core element of digital ...
read it
-
What Do We Really Need? Degenerating U-Net on Retinal Vessel Segmentation
Retinal vessel segmentation is an essential step for fundus image analys...
read it
-
Superpixel-Based Background Recovery from Multiple Images
In this paper, we propose an intuitive method to recover background from...
read it
-
Field of View Extension in Computed Tomography Using Deep Learning Prior
In computed tomography (CT), data truncation is a common problem. Images...
read it
-
Image Quality Assessment for Rigid Motion Compensation
Diagnostic stroke imaging with C-arm cone-beam computed tomography (CBCT...
read it
-
Learning to Avoid Poor Images: Towards Task-aware C-arm Cone-beam CT Trajectories
Metal artifacts in computed tomography (CT) arise from a mismatch betwee...
read it
-
Magnetic Resonance Fingerprinting Reconstruction Using Recurrent Neural Networks
Magnetic Resonance Fingerprinting (MRF) is an imaging technique acquirin...
read it
-
A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation Systems
For complex segmentation tasks, the achievable accuracy of fully automat...
read it
-
Automated Multi-sequence Cardiac MRI Segmentation Using Supervised Domain Adaptation
Left ventricle segmentation and morphological assessment are essential f...
read it
-
Data Consistent Artifact Reduction for Limited Angle Tomography with Deep Learning Prior
Robustness of deep learning methods for limited angle tomography is chal...
read it
-
Deep Generalized Max Pooling
Global pooling layers are an essential part of Convolutional Neural Netw...
read it
-
Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides
Purpose: Exercise-induced pulmonary hemorrhage (EIPH) is a common syndro...
read it
-
Multi-task Localization and Segmentation for X-ray Guided Planning in Knee Surgery
X-ray based measurement and guidance are commonly used tools in orthopae...
read it
-
A Divide-and-Conquer Approach towards Understanding Deep Networks
Deep neural networks have achieved tremendous success in various fields ...
read it
-
RinQ Fingerprinting: Recurrence-informed Quantile Networks for Magnetic Resonance Fingerprinting
Recently, Magnetic Resonance Fingerprinting (MRF) was proposed as a quan...
read it
-
Analysis by Adversarial Synthesis -- A Novel Approach for Speech Vocoding
Classical parametric speech coding techniques provide a compact represen...
read it
-
A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT
Automatic segmentation of organs-at-risk (OAR) in computed tomography (C...
read it
-
Multi-task Learning for Chest X-ray Abnormality Classification on Noisy Labels
Chest X-ray (CXR) is the most common X-ray examination performed in dail...
read it
-
Dilated deeply supervised networks for hippocampus segmentation in MRI
Tissue loss in the hippocampi has been heavily correlated with the progr...
read it
-
Transferability of Deep Learning Algorithms for Malignancy Detection in Confocal Laser Endomicroscopy Images from Different Anatomical Locations of the Upper Gastrointestinal T
Squamous Cell Carcinoma (SCC) is the most common cancer type of the epit...
read it
-
Field of Interest Prediction for Computer-Aided Mitotic Count
Manual counts of mitotic figures, which are determined in the tumor regi...
read it
-
The Random Forest Classifier in WEKA: Discussion and New Developments for Imbalanced Data
Data analysis and machine learning have become an integrative part of th...
read it
-
Balanced Random Forest Classifier in WEKA
Data analysis and machine learning have become an integrative part of th...
read it
-
Towards Fast Biomechanical Modeling of Soft Tissue Using Neural Networks
To date, the simulation of organ deformations for applications like ther...
read it
-
A 3-D Projection Model for X-ray Dark-field Imaging
Talbot-Lau X-ray phase-contrast imaging is a novel imaging modality, whi...
read it
-
Field Of Interest Proposal for Augmented Mitotic Cell Count: Comparison of two Convolutional Networks
Most tumor grading systems for human as for veterinary histopathology ar...
read it
-
A Gentle Introduction to Deep Learning in Medical Image Processing
This paper tries to give a gentle introduction to deep learning in medic...
read it
-
Augmented Mitotic Cell Count using Field Of Interest Proposal
Histopathological prognostication of neoplasia including most tumor grad...
read it
-
Bridging the Simulated-to-Real Gap: Benchmarking Super-Resolution on Real Data
Capturing ground truth data to benchmark super-resolution (SR) is challe...
read it
-
A Multi-task Framework for Skin Lesion Detection and Segmentation
Early detection and segmentation of skin lesions is crucial for timely d...
read it
-
Dilated Convolutions in Neural Networks for Left Atrial Segmentation in 3D Gadolinium Enhanced-MRI
Segmentation of the left atrial chamber and assessing its morphology, ar...
read it
-
User Loss -- A Forced-Choice-Inspired Approach to Train Neural Networks directly by User Interaction
In this paper, we investigate whether is it possible to train a neural n...
read it
-
Deriving Neural Network Architectures using Precision Learning: Parallel-to-fan beam Conversion
In this paper, we derive a neural network architecture based on an analy...
read it
-
Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images
Electroluminescence (EL) imaging is a useful modality for the inspection...
read it
-
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction
Deep learning approaches have shown promising performance for compressed...
read it
-
SkinNet: A Deep Learning Framework for Skin Lesion Segmentation
There has been a steady increase in the incidence of skin cancer worldwi...
read it
-
Augmented Reality-based Feedback for Technician-in-the-loop C-arm Repositioning
Interventional C-arm imaging is crucial to percutaneous orthopedic proce...
read it
-
Metric-Driven Learning of Correspondence Weighting for 2-D/3-D Image Registration
Registration for pre-operative 3-D images to intra-operative 2-D fluoros...
read it
-
Non-deterministic Behavior of Ranking-based Metrics when Evaluating Embeddings
Embedding data into vector spaces is a very popular strategy of pattern ...
read it
-
Segmentation of Photovoltaic Module Cells in Electroluminescence Images
High resolution electroluminescence (EL) images captured in the infrared...
read it
-
Action Learning for 3D Point Cloud Based Organ Segmentation
We propose a novel point cloud based 3D organ segmentation pipeline util...
read it