Related references
Note: Only part of the references are listed.
Review
Computer Science, Artificial Intelligence
Jun Li et al.
Summary: This paper reviews the research progress and applications of Transformers in medical imaging. After comparing Transformers with convolutional neural networks, the key defining properties of Transformers and the combination of Transformers and CNNs are highlighted. The latest research progress in medical image segmentation, recognition, detection, registration, reconstruction, enhancement, etc. are comprehensively reviewed, and the organization of the review based on key defining properties and architectural type provides the readers with the best understanding of the rationale behind the reviewed approaches.
MEDICAL IMAGE ANALYSIS
(2023)
Article
Surgery
Elizabeth R. Benjamin et al.
Summary: The primary aim of this study was to evaluate the role of the initial pelvic X-ray in identifying significant pelvic fractures. The study found that pelvic X-ray had good sensitivity in detecting symphysis diastasis but lower sensitivity in other types of pelvic fractures. Therefore, CT scan evaluation should be performed in patients with a suspicious mechanism or clinical suspicion of pelvic fracture.
AMERICAN JOURNAL OF SURGERY
(2022)
Article
Engineering, Biomedical
Asma Alzaid et al.
Summary: This study aims to assess the performance of existing classification systems and object detection systems in diagnosing fractures in proximity of joint implants. By collecting a large dataset of X-ray images and annotating them, it was found that the deep learning-based approach showed promising results in detecting, classifying, and localizing fractures.
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
(2022)
Article
Computer Science, Artificial Intelligence
Gao Huang et al.
Summary: Recent work has shown that adding shorter connections in convolutional networks can make the network deeper, more accurate, and more efficient in training. This paper introduces Dense Convolutional Network (DenseNet), which connects each layer to every other layer in a feed-forward manner. DenseNets alleviate the vanishing-gradient problem, encourage feature reuse, and improve parameter efficiency, leading to significant improvements in object recognition tasks.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Wenkong Wang et al.
Summary: This study proposes a method based on GAN and WrisNet to improve the detection performance of wrist and finger fractures. Experimental results show that this method has significant improvement in average precision compared to other mainstream frameworks, and it can be implemented in real clinical environment easily.
NEURAL COMPUTING & APPLICATIONS
(2022)
Review
Engineering, Biomedical
Jiangchang Xu et al.
Summary: This study reviews the application of deep learning-based medical image computing (MIC) in head and neck surgery. By analyzing relevant literature, the use of deep learning methods in segmentation, landmark detection, and registration of head and neck medical images is summarized. The advantages, differences, and shortcomings of deep learning in these areas are discussed, and future development directions are proposed.
PHYSICS IN MEDICINE AND BIOLOGY
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Ze Liu et al.
Summary: This paper introduces a Transformer architecture with a bias towards locality in video recognition, achieving a better balance between speed and accuracy compared to global self-attention mechanisms; by adapting the Swin Transformer and leveraging pre-trained models, it achieves state-of-the-art accuracy on various video recognition benchmarks.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022)
(2022)
Proceedings Paper
Neuroimaging
Debayan Bhattacharya et al.
Summary: This research focuses on using deep learning and MRI images to detect anomalies in the paranasal sinus system. By combining contrastive loss and cross-entropy loss, the study proposes a novel learning paradigm that improves label efficiency and classifier accuracy.
MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION, MICCAI 2022, PT III
(2022)
Article
Computer Science, Artificial Intelligence
Mohammad Shorfuzzaman et al.
Summary: An AI system based on deep meta learning was proposed to accelerate analysis of chest X-ray (CXR) images for automatic detection of COVID-19 cases. The model integrates contrastive learning and a fine-tuned pre-trained ConvNet encoder to capture unbiased feature representations, achieving 95.6% accuracy and AUC of 0.97 in diagnosing COVID-19 from CXR images.
PATTERN RECOGNITION
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
David Dreizin et al.
Summary: The triplanar parallel concatenated network with ResNeXt-50 backbone accurately distinguishes rotational and translational instability in pelvic fractures. It achieved a high accuracy of 85% for translational instability and 74% for rotational instability, with a mean inference time of less than 0.1 s per test image.
JOURNAL OF DIGITAL IMAGING
(2021)
Article
Computer Science, Interdisciplinary Applications
David Xinzheyang Li et al.
Summary: This study quantified the degree of regional pelvic symmetry using computer-based methods and found that pelvic regions can be considered highly symmetric locally but with a degree of global asymmetry. The pubis and ischium regions showed high local symmetry, while the acetabular and iliac regions exhibited similar levels of symmetry with the two methods used. These results may have implications for assessing the feasibility of patient-specific implants in unilateral pelvic fracture fixation.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Xavier Rafael-Palou et al.
Summary: This study introduces a new method based on a 3D siamese neural network for re-identification of nodules in a pair of CT scans of the same patient. The experimental results show that the method has high accuracy and sensitivity.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Computer Science, Interdisciplinary Applications
Alberto Rossi et al.
Summary: Multi-parametric prostate MRI (mpMRI) is a powerful tool for diagnosing prostate cancer, but can be challenging to interpret. This study introduces a new supervised siamese deep learning architecture for handling multi-modal and multi-view MR images with similar PIRADS scores, showing significantly improved performance compared to established deep learning-based CBIRs. The proposed multi-view siamese network is versatile and can be widely used in diagnostic medical imaging retrieval.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2021)
Article
Computer Science, Artificial Intelligence
R. Han et al.
Summary: The study introduces a multi-body registration framework for pelvic fracture reduction planning and intraoperative guidance using preoperative CT and routine 2D fluoroscopy. The framework showed promising results in simulation and clinical feasibility studies, with improved accuracy and reduced radiation exposure, demonstrating its potential in enhancing pelvic fracture reduction outcomes in a variety of cases.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Multidisciplinary Sciences
Chi-Tung Cheng et al.
Summary: Pelvic radiographs are crucial for detecting proximal femur and pelvis injuries in trauma patients, yet current algorithms are limited in accurately detecting all trauma-related radiographic findings. This study introduces PelviXNet, a deep learning algorithm trained with weakly supervised point annotation, which demonstrates high accuracy and sensitivity in a clinical population test set.
NATURE COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Michal Byra et al.
Summary: This study utilized deep learning methods for early prediction of response to neoadjuvant chemotherapy in breast cancer, proposing two transfer learning techniques and investigating two prediction tasks. Results showed the feasibility of using transfer learning with deep CNNs for NAC response prediction in ultrasound imaging.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2021)
Article
Engineering, Biomedical
Pengbo Liu et al.
Summary: This study curated a large pelvic CT dataset from multiple sources, developed a deep learning method for automatic pelvic bone segmentation, and proposed a post-processor based on the signed distance function (SDF). Experimental results showed high accuracy and improved Hausdorff distance compared to traditional methods.
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
(2021)
Article
Computer Science, Artificial Intelligence
Javad Fotouhi et al.
Summary: This paper presents a novel methodology for detecting imperfect bilateral symmetry in CT images of human anatomy, with a focus on the importance of pelvic bone symmetry in treating traumatic fractures. The mathematical basis and algorithm enhance the accuracy and robustness of image processing, demonstrating the validity of the proposed method in various common fracture cases.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Computer Science, Artificial Intelligence
Adrian Luque-Luque et al.
Summary: Planning fracture reduction is crucial for reducing surgery time and enhancing recovery, with no fully automatic methods available yet. This paper introduces an approach aiming to minimize specialist intervention by identifying the complete fracture zone and utilizing a modified ICP algorithm to work with fragment distance. The proposed technique has been validated using a VR framework, showing significant improvement over existing methods.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Optics
Rinisha Bagaria et al.
Summary: This paper proposes a machine learning-based system for accurately detecting and classifying fractured and non-fractured bone images, consisting of four principal phases: image acquisition, pre-processing, feature extracting, and classification. The classification using Support Vector Machine (SVM) is found to be more accurate with a classification rate of 94%, which is 2% higher than the Error Backpropagation Neural Network (EBP-NN) technique.
Article
Multidisciplinary Sciences
Kazutoshi Ukai et al.
Summary: The study proposed an automated method to detect pelvic fractures on 3D-CT using multiple YOLOv3 models in parallel to detect 2D fracture candidates in different orientations and integrate them to obtain the 3D fracture region. The method showed promising performance in validation phase.
SCIENTIFIC REPORTS
(2021)
Article
Computer Science, Interdisciplinary Applications
Maha S. Ead et al.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2020)
Article
Computer Science, Artificial Intelligence
Deepa Joshi et al.
ARTIFICIAL INTELLIGENCE REVIEW
(2020)
Article
Computer Science, Interdisciplinary Applications
Lihao Liu et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2020)
Article
Multidisciplinary Sciences
Changhwan Lee et al.
SCIENTIFIC REPORTS
(2020)
Article
Computer Science, Interdisciplinary Applications
Yi-Jie Huang et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2020)
Article
Medicine, General & Internal
Liang Jin et al.
Article
Surgery
Monika Garcia et al.
Proceedings Paper
Engineering, Biomedical
Vikash Gupta et al.
2020 IEEE 17TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2020)
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Yirui Wang et al.
MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2019, PT VI
(2019)
Article
Biology
Naofumi Tomita et al.
COMPUTERS IN BIOLOGY AND MEDICINE
(2018)
Article
Orthopedics
H. Schmal et al.
BONE & JOINT JOURNAL
(2018)
Review
Clinical Neurology
Ricardo Rodrigues-Pinto et al.
GLOBAL SPINE JOURNAL
(2017)
Article
Computer Science, Interdisciplinary Applications
Felix Paulano-Godino et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2017)
Review
Computer Science, Interdisciplinary Applications
Oishila Bandyopadhyay et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2016)
Article
Critical Care Medicine
Huixiang Wang et al.
INJURY-INTERNATIONAL JOURNAL OF THE CARE OF THE INJURED
(2016)
Article
Engineering, Biomedical
Jan Buschbaum et al.
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
(2015)
Article
Emergency Medicine
James F. Holmes et al.
AMERICAN JOURNAL OF EMERGENCY MEDICINE
(2012)
Article
Engineering, Biomedical
Toshiyuki Okada et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2009)
