Advances in medical image analysis with vision transformers: a comprehensive review
The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …
has recently also triggered broad interest in Computer Vision. Among other merits …
A vertebral segmentation dataset with fracture grading
MT Löffler, A Sekuboyina, A Jacob, AL Grau… - Radiology: Artificial …, 2020 - pubs.rsna.org
Keywords: CT, Computer Aided Diagnosis (CAD), Computer Applications-General
(Informatics), Convolutional Neural Network (CNN), Diagnosis, Neural Networks …
(Informatics), Convolutional Neural Network (CNN), Diagnosis, Neural Networks …
Cutting-edge 3D medical image segmentation methods in 2020: Are happy families all alike?
J Ma - arxiv preprint arxiv:2101.00232, 2021 - arxiv.org
Segmentation is one of the most important and popular tasks in medical image analysis,
which plays a critical role in disease diagnosis, surgical planning, and prognosis evaluation …
which plays a critical role in disease diagnosis, surgical planning, and prognosis evaluation …
A computed tomography vertebral segmentation dataset with anatomical variations and multi-vendor scanner data
With the advent of deep learning algorithms, fully automated radiological image analysis is
within reach. In spine imaging, several atlas-and shape-based as well as deep learning …
within reach. In spine imaging, several atlas-and shape-based as well as deep learning …
Localization and edge-based segmentation of lumbar spine vertebrae to identify the deformities using deep learning models
The lumbar spine plays a very important role in our load transfer and mobility. Vertebrae
localization and segmentation are useful in detecting spinal deformities and fractures …
localization and segmentation are useful in detecting spinal deformities and fractures …
CTSpine1K: a large-scale dataset for spinal vertebrae segmentation in computed tomography
Spine-related diseases have high morbidity and cause a huge burden of social cost. Spine
imaging is an essential tool for noninvasively visualizing and assessing spinal pathology …
imaging is an essential tool for noninvasively visualizing and assessing spinal pathology …
Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient
Metrics optimized in complex machine learning tasks are often selected in an ad-hoc
manner. It is unknown how they align with human expert perception. We explore the …
manner. It is unknown how they align with human expert perception. We explore the …
Domain generalizer: A few-shot meta learning framework for domain generalization in medical imaging
Deep learning models perform best when tested on target (test) data domains whose
distribution is similar to the set of source (train) domains. However, model generalization can …
distribution is similar to the set of source (train) domains. However, model generalization can …
Opportunistic osteoporosis screening reveals low bone density in patients with screw loosening after lumbar semi-rigid instrumentation: a case-control study
Objective Decreased bone mineral density (BMD) impairs screw purchase in trabecular
bone and can cause screw loosening following spinal instrumentation. Existing computed …
bone and can cause screw loosening following spinal instrumentation. Existing computed …
Vertebral deformity measurements at MRI, CT, and radiography using deep learning
Purpose To construct and evaluate the efficacy of a deep learning system to rapidly and
automatically locate six vertebral landmarks, which are used to measure vertebral body …
automatically locate six vertebral landmarks, which are used to measure vertebral body …