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Radiology, Nuclear Medicine & Medical Imaging
Taylor R. Moen et al.
Summary: This dataset consists of CT images and projection data from patient exams at routine clinical doses and simulated lower doses. Collected under local ethics committee approval, it includes data from 299 patient CT exams of three types. The library allows for development and validation of new CT reconstruction and denoising algorithms.
Article
Computer Science, Artificial Intelligence
Linh T. Duong et al.
Summary: This study aims to early detect tuberculosis using medical imaging and artificial intelligence technology, proposing a solution for detecting tuberculosis from chest X-ray images and utilizing various deep neural network techniques, achieving better performance compared to existing methods.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Emily B. Tsai et al.
Summary: The COVID-19 pandemic is a global health emergency, and chest X-rays and CT scans play a vital role in detecting and managing infected patients. The RSNA and Society of Thoracic Radiology collaborated to develop the RICORD database, which provides annotated COVID-19 imaging data for research and education.
Article
Computer Science, Interdisciplinary Applications
Victor M. Campello et al.
Summary: The emergence of deep learning has advanced cardiac magnetic resonance segmentation, yet current models lack generalizability. A recent competition emphasized the importance of data augmentation in training deep learning models and provided new data resources for future research.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2021)
Article
Biology
Tawsifur Rahman et al.
Summary: Computer-aided diagnosis for fast and reliable detection of COVID-19 using a large X-ray dataset, various image enhancement techniques, and deep learning models has shown promising results in this study.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Computer Science, Artificial Intelligence
Anjany Sekuboyina et al.
Summary: Vertebral labelling and segmentation are essential tasks in medical image processing, and the VERSE challenge evaluated 25 algorithms on two datasets containing 374 CT scans. The key takeaway is that the performance of an algorithm in correctly identifying rare anatomical variations is crucial for labelling and segmenting spine scans.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Computer Science, Artificial Intelligence
Saidi Guo et al.
Summary: This paper proposes multi-level semantic adaptation (MSA) for few-shot segmentation on cardiac image sequences, addressing spatial-temporal distribution bias and long-term information bias through domain adaptation and weight adaptation at sequence-level, frame-level, and pixel-level to improve model adaptation and border feature discrimination.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Engineering, Biomedical
Yanan Wu et al.
Summary: The study proposed a method for classifying subtypes of emphysema using a vision transformer model, achieving high accuracy in the lab's own dataset by extracting key information from CT images and utilizing pre-trained models.
PHYSICS IN MEDICINE AND BIOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Yousry AbdulAzeem et al.
Summary: With advances in healthcare, the diagnosis of Alzheimer's disease has become increasingly important. Studies utilizing brain MRI scans and deep learning algorithms have shown promising results, aiding in the early and accurate classification of Alzheimer's disease.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Health Care Sciences & Services
Qixuan Sun et al.
Summary: This study proposes a hybrid multimodal segmentation method based on Transformer and CNN, showing superior performance over traditional fully CNN methods in most evaluation metrics. The study also analyzes the influence of Transformer depth on performance, visualizes the results, and explores how the hybrid methods improve segmentations.
JOURNAL OF HEALTHCARE ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
A. Emre Kavur et al.
Summary: Abdominal organ segmentation has long been a comprehensive research field, with recent developments in deep learning introducing new state-of-the-art segmentation systems. However, the effects of DL model properties and parameters on performance are still difficult to interpret, and multi-tasking DL models often perform worse compared to organ-specific ones.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Oncology
Xuming Chen et al.
Summary: This study introduced a deep learning-based automatic segmentation algorithm, WBNet, which accurately and efficiently delineates major organs at risk (OARs) on CT images. WBNet outperformed other AS algorithms in terms of DSC values and delineation time, showing great effectiveness in clinical practice.
RADIOTHERAPY AND ONCOLOGY
(2021)
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Multidisciplinary Sciences
Parnian Afshar et al.
Summary: COVID-19 has significantly impacted over 200 countries worldwide, leading to the emergence of a new CT scan dataset, COVID-CT-MD, which shows potential in advancing research and developing advanced ML and DNN solutions for COVID-19.
Article
Engineering, Biomedical
Mohammad Rahimzadeh et al.
Summary: This paper presents a high-speed and accurate fully-automated method for detecting COVID-19 from chest CT scan images. By introducing a new dataset and algorithm, the system achieves significant improvements in classification accuracy and speed.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Computer Science, Artificial Intelligence
Alberto Signoroni et al.
Summary: This study presents an end-to-end deep learning architecture for predicting the degree of lung compromise in COVID-19 patients on Chest X-ray images. The proposed semi-quantitative scoring system shows significant prognostic value and outperforms human annotators. The BS-Net demonstrates high accuracy and self-attentive behavior, showcasing its potential for computer-assisted monitoring in clinical settings.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Computer Science, Information Systems
Ziduo Yang et al.
Summary: A weakly supervised method based on generative adversarial network for COVID-19 lesion localization using only image-level labels was proposed in this study. By incorporating a novel feature match strategy, the method achieved significantly better results compared to other approaches.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2021)
Article
Medicine, General & Internal
Yin Dai et al.
Summary: The article discusses the advantages and limitations of convolutional neural networks (CNN) and transformers in medical image analysis, proposing a method called TransMed that combines CNN and transformer for multi-modal medical image classification. The approach achieved significant performance improvement on two datasets and outperformed existing CNN-based models.
Proceedings Paper
Computer Science, Artificial Intelligence
Ishan Misra et al.
Summary: 3DETR is an end-to-end Transformer based object detection model for 3D point clouds, requiring minimal modifications to the vanilla Transformer block and outperforming specialized architectures on the ScanNetV2 dataset. It is applicable to tasks beyond detection and can serve as a building block for future research.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Hao Tang et al.
Summary: This work proposes a new framework for few-shot medical image segmentation based on prototypical networks, achieving substantial improvement over state-of-the-art methods in experiments by designing a context relation encoder and a recurrent mask refinement module.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Sharif Amit Kamran et al.
Summary: This study introduces a conditional GAN with image generation capabilities to synthesize FA images and predict retinal degeneration simultaneously, addressing the issue of imaging retinal vasculature and predicting abnormalities. The semi-supervised approach used for training and validation show its superiority over recent generative networks.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2021)
(2021)
Article
Engineering, Electrical & Electronic
Zechao Wang et al.
Summary: A dual-stage model-driven scheme is proposed to compensate dynamic pressure measurement by deriving DSSCs from axial governing equations of pipes, considering both thin-walled and thick-walled pipes, and calibrating physical parameters to minimize the residual between experimental and theoretical results. The compensated dynamic pressure based on the relationship between DSSCs and SSSCs shows significantly reduced relative error in an industrial hydraulic pipe system, validating the proposed compensation method.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
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Radiology, Nuclear Medicine & Medical Imaging
Ross W. Filice et al.
JOURNAL OF DIGITAL IMAGING
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Computer Science, Artificial Intelligence
Jose Ignacio Orlando et al.
MEDICAL IMAGE ANALYSIS
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Computer Science, Interdisciplinary Applications
Neeraj Kumar et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2020)
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Radiology, Nuclear Medicine & Medical Imaging
Andrea Borghesi et al.
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Multidisciplinary Sciences
David Ouyang et al.
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Computer Science, Artificial Intelligence
Chunwei Tian et al.
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K. M. Faizullah Fuhad et al.
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Deng-Ping Fan et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
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Jeya Maria Jose Valanarasu et al.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2020)
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Acoustics
Aleksandar Vakanski et al.
ULTRASOUND IN MEDICINE AND BIOLOGY
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Aurelia Bustos et al.
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Shivang Desai et al.
Proceedings Paper
Computer Science, Artificial Intelligence
Tony C. W. Mok et al.
2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR)
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Computer Science, Artificial Intelligence
Venkateswararao Cherukuri et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2020)
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Multidisciplinary Sciences
Walid Al-Dhabyani et al.
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Computer Science, Information Systems
Tawsifur Rahman et al.
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Computer Science, Information Systems
Muhammad E. H. Chowdhury et al.
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Computer Science, Interdisciplinary Applications
Peter Naylor et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2019)
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Computer Science, Artificial Intelligence
Xiahai Zhuang
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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Biochemical Research Methods
Mohamed Amgad et al.
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Computer Science, Artificial Intelligence
Felix Ambellan et al.
MEDICAL IMAGE ANALYSIS
(2019)
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Medicine, General & Internal
Jakob Nikolas Kather et al.
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Computer Science, Interdisciplinary Applications
Majd Zreik et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2019)
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Computer Science, Interdisciplinary Applications
Li Wang et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2019)
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Biochemical Research Methods
Juan C. Caicedo et al.
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Computer Science, Interdisciplinary Applications
Xiangrui Yin et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
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Computer Science, Artificial Intelligence
Simon Graham et al.
MEDICAL IMAGE ANALYSIS
(2019)
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Engineering, Biomedical
Max-Heinrich Laves et al.
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Kai Xu et al.
2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019)
(2019)
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Computer Science, Artificial Intelligence
Hongming Shan et al.
NATURE MACHINE INTELLIGENCE
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Biochemistry & Molecular Biology
Daniel S. Kermany et al.
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Computer Science, Interdisciplinary Applications
Olivier Bernard et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2018)
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Computer Science, Interdisciplinary Applications
Qingsong Yang et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2018)
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Radiology, Nuclear Medicine & Medical Imaging
Tufve Nyholm et al.
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Computer Science, Information Systems
Moi Hoon Yap et al.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2018)
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Multidisciplinary Sciences
Sivaramakrishnan Rajaraman et al.
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Multidisciplinary Sciences
Sook-Lei Liew et al.
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Multidisciplinary Sciences
Philipp Tschandl et al.
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Multidisciplinary Sciences
Anubha Gupta et al.
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Medicine, General & Internal
Nicholas Bien et al.
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Radiology, Nuclear Medicine & Medical Imaging
Ke Yan et al.
JOURNAL OF MEDICAL IMAGING
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Computer Science, Interdisciplinary Applications
Zhipeng Jia et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
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Computer Science, Interdisciplinary Applications
Hu Chen et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
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Computer Science, Interdisciplinary Applications
Neeraj Kumar et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
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Medicine, General & Internal
Babak Ehteshami Bejnordi et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
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Oskar Maier et al.
MEDICAL IMAGE ANALYSIS
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Computer Science, Artificial Intelligence
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MEDICAL IMAGE ANALYSIS
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Radiology, Nuclear Medicine & Medical Imaging
Cynthia H. McCollough et al.
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Health Care Sciences & Services
David Vazquez et al.
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Spyridon Bakas et al.
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Amber L. Simpson et al.
ANNALS OF SURGICAL ONCOLOGY
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Proceedings Paper
Computer Science, Artificial Intelligence
Simon Jegou et al.
2017 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW)
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Gao Huang et al.
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017)
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Kaiming He et al.
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV)
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Dina Demner-Fushman et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
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Nima Tajbakhsh et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
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Xiahai Zhuang et al.
MEDICAL IMAGE ANALYSIS
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Jakob Nikolas Kather et al.
SCIENTIFIC REPORTS
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Computer Science, Interdisciplinary Applications
Bjoern H. Menze et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
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Mathematical & Computational Biology
Adrienne M. Mendrik et al.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
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Mark Everingham et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION
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Geert Litjens et al.
MEDICAL IMAGE ANALYSIS
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Hugo J. W. L. Aerts et al.
NATURE COMMUNICATIONS
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JOURNAL OF DIGITAL IMAGING
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W. P. Segars et al.
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Ines C. Moreira et al.
ACADEMIC RADIOLOGY
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B. Zheng et al.
BRITISH JOURNAL OF RADIOLOGY
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Shirin Hajeb Mohammad Alipour et al.
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
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Muhammad Moazam Fraz et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
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Radiology, Nuclear Medicine & Medical Imaging
Samuel G. Armato et al.
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PROGRESS IN NEUROBIOLOGY
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Ophthalmology
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J Staal et al.
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A Hoover et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2000)
