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09/06/2023
Expert Uncertainty and Severity Aware Chest X-Ray Classification by Multi-Relationship Graph Learning
Patients undergoing chest X-rays (CXR) often endure multiple lung diseas...
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08/17/2023
How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers?
Pruning has emerged as a powerful technique for compressing deep neural ...
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07/31/2023
C-DARL: Contrastive diffusion adversarial representation learning for label-free blood vessel segmentation
Blood vessel segmentation in medical imaging is one of the essential ste...
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07/22/2023
Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering
To contribute to automating the medical vision-language model, we propos...
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07/11/2023
Improving Segmentation and Detection of Lesions in CT Scans Using Intensity Distribution Supervision
We propose a method to incorporate the intensity information of a target...
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06/14/2023
Utilizing Longitudinal Chest X-Rays and Reports to Pre-Fill Radiology Reports
Despite the reduction in turn-around times in radiology reports with the...
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08/29/2022
Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study
Imaging exams, such as chest radiography, will yield a small set of comm...
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07/29/2022
Improving Small Lesion Segmentation in CT Scans using Intensity Distribution Supervision: Application to Small Bowel Carcinoid Tumor
Finding small lesions is very challenging due to lack of noticeable feat...
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07/29/2022
Graph-Based Small Bowel Path Tracking with Cylindrical Constraints
We present a new graph-based method for small bowel path tracking based ...
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06/29/2022
Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations
Small bowel path tracking is a challenging problem considering its many ...
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03/31/2022
Universal Lymph Node Detection in T2 MRI using Neural Networks
Purpose: Identification of abdominal Lymph Nodes (LN) that are suspiciou...
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11/09/2021
Universal Lesion Detection in CT Scans using Neural Network Ensembles
In clinical practice, radiologists are reliant on the lesion size when d...
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11/09/2021
Lymph Node Detection in T2 MRI with Transformers
Identification of lymph nodes (LN) in T2 Magnetic Resonance Imaging (MRI...
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10/01/2021
A Graph-theoretic Algorithm for Small Bowel Path Tracking in CT Scans
We present a novel graph-theoretic method for small bowel path tracking....
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04/12/2021
Common Limitations of Image Processing Metrics: A Picture Story
While the importance of automatic image analysis is increasing at an eno...
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07/19/2020
E^2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans
Developing an effective liver and liver tumor segmentation model from CT...
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07/16/2020
Deep Small Bowel Segmentation with Cylindrical Topological Constraints
We present a novel method for small bowel segmentation where a cylindric...
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07/14/2020
Cross-Domain Medical Image Translation by Shared Latent Gaussian Mixture Model
Current deep learning based segmentation models often generalize poorly ...
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07/12/2020
Deep Network Interpolation for Accelerated Parallel MR Image Reconstruction
We present a deep network interpolation strategy for accelerated paralle...
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06/11/2020
COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature
The latest threat to global health is the COVID-19 outbreak. Although th...
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05/22/2020
Image Translation by Latent Union of Subspaces for Cross-Domain Plaque Detection
Calcified plaque in the aorta and pelvic arteries is associated with cor...
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02/08/2020
Bone Suppression on Chest Radiographs With Adversarial Learning
Dual-energy (DE) chest radiography provides the capability of selectivel...
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01/28/2020
Accurately identifying vertebral levels in large datasets
The vertebral levels of the spine provide a useful coordinate system whe...
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01/24/2020
Weakly Supervised Lesion Co-segmentation on CT Scans
Lesion segmentation in medical imaging serves as an effective tool for a...
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01/23/2020
Weakly-Supervised Lesion Segmentation on CT Scans using Co-Segmentation
Lesion segmentation on computed tomography (CT) scans is an important st...
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12/18/2019
Σ-net: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image Reconstruction
Purpose: To systematically investigate the influence of various data con...
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12/11/2019
Σ-net: Ensembled Iterative Deep Neural Networks for Accelerated Parallel MR Image Reconstruction
We explore an ensembled Σ-net for fast parallel MR imaging, including pa...
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08/21/2019
TUNA-Net: Task-oriented UNsupervised Adversarial Network for Disease Recognition in Cross-Domain Chest X-rays
In this work, we exploit the unsupervised domain adaptation problem for ...
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08/12/2019
MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation
When reading medical images such as a computed tomography (CT) scan, rad...
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04/30/2019
A self-attention based deep learning method for lesion attribute detection from CT reports
In radiology, radiologists not only detect lesions from the medical imag...
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04/19/2019
XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation
This paper proposes a novel framework for lung segmentation in chest X-r...
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04/09/2019
Holistic and Comprehensive Annotation of Clinically Significant Findings on Diverse CT Images: Learning from Radiology Reports and Label Ontology
In radiologists' routine work, one major task is to read a medical image...
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03/05/2019
Abnormal Chest X-ray Identification With Generative Adversarial One-Class Classifier
Being one of the most common diagnostic imaging tests, chest radiography...
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03/04/2019
Fine-grained lesion annotation in CT images with knowledge mined from radiology reports
In radiologists' routine work, one major task is to read a medical image...
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02/25/2019
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
Semantic segmentation of medical images aims to associate a pixel with a...
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02/23/2019
Spatial-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data
Prognostic tumor growth modeling via medical imaging observations is a c...
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01/18/2019
ULDor: A Universal Lesion Detector for CT Scans with Pseudo Masks and Hard Negative Example Mining
Automatic lesion detection from computed tomography (CT) scans is an imp...
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07/19/2018
Attention-Guided Curriculum Learning for Weakly Supervised Classification and Localization of Thoracic Diseases on Chest Radiographs
In this work, we exploit the task of joint classification and weakly sup...
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07/18/2018
CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement
Automated lesion segmentation from computed tomography (CT) is an import...
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07/02/2018
Accurate Weakly-Supervised Deep Lesion Segmentation using Large-Scale Clinical Annotations: Slice-Propagated 3D Mask Generation from 2D RECIST
Volumetric lesion segmentation from computed tomography (CT) images is a...
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06/25/2018
3D Context Enhanced Region-based Convolutional Neural Network for End-to-End Lesion Detection
Detecting lesions from computed tomography (CT) scans is an important bu...
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06/25/2018
Semi-Automatic RECIST Labeling on CT Scans with Cascaded Convolutional Neural Networks
Response evaluation criteria in solid tumors (RECIST) is the standard me...
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01/25/2018
DeepPap: Deep Convolutional Networks for Cervical Cell Classification
Automation-assisted cervical screening via Pap smear or liquid-based cyt...
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01/25/2018
Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST
Volumetric lesion segmentation via medical imaging is a powerful means t...
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01/25/2018
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans
This paper reports Deep LOGISMOS approach to 3D tumor segmentation by in...
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01/25/2018
Self-Learning to Detect and Segment Cysts in Lung CT Images without Manual Annotation
Image segmentation is a fundamental problem in medical image analysis. I...
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01/25/2018
Convolutional Invasion and Expansion Networks for Tumor Growth Prediction
Tumor growth is associated with cell invasion and mass-effect, which are...
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01/12/2018
TieNet: Text-Image Embedding Network for Common Thorax Disease Classification and Reporting in Chest X-rays
Chest X-rays are one of the most common radiological examinations in dai...
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10/04/2017
DeepLesion: Automated Deep Mining, Categorization and Detection of Significant Radiology Image Findings using Large-Scale Clinical Lesion Annotations
Extracting, harvesting and building large-scale annotated radiological i...
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07/12/2017