Anatomy
320 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Anatomy
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Libraries
Use these libraries to find Anatomy models and implementations
BIG-bench
Most implemented papers
Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem
JoHof/lungmask
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We compared four generic deep learning approaches trained on various datasets and two readily available lung segmentation algorithms.
Disentangled Representation Learning in Cardiac Image Analysis
agis85/anatomy_modality_decomposition
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We can venture further and consider that a medical image naturally factors into some spatial factors depicting anatomy and factors that denote the imaging characteristics.
Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-supervised Learning
This paper introduces a new concept called "transferable visual words" (TransVW), aiming to achieve annotation efficiency for deep learning in medical image analysis.
AeroPath: An airway segmentation benchmark dataset with challenging pathology
puzzled-hui/atm-22-related-work
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In this study, we introduce a new public benchmark dataset (AeroPath), consisting of 27 CT images from patients with pathologies ranging from emphysema to large tumors, with corresponding trachea and bronchi annotations.
On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models
On the other hand, ConvNet potentials learned with non-convergent MCMC do not have a valid steady-state and cannot be considered approximate unnormalized densities of the training data because long-run MCMC samples differ greatly from observed images.
Deep Active Learning for Axon-Myelin Segmentation on Histology Data
neuropoly/deep-active-learning
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In this paper we provide a framework for Deep Active Learning applied to a real-world scenario.
End-to-End Variational Networks for Accelerated MRI Reconstruction
The slow acquisition speed of magnetic resonance imaging (MRI) has led to the development of two complementary methods: acquiring multiple views of the anatomy simultaneously (parallel imaging) and acquiring fewer samples than necessary for traditional signal processing methods (compressed sensing).
KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations
jeya-maria-jose/KiU-Net-pytorch
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Due to its excellent performance, U-Net is the most widely used backbone architecture for biomedical image segmentation in the recent years.
Reinforcement Learning with Random Delays
Action and observation delays commonly occur in many Reinforcement Learning applications, such as remote control scenarios.
Recurrent Variational Network: A Deep Learning Inverse Problem Solver applied to the task of Accelerated MRI Reconstruction
directgroup/direct
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CVPR 2022
Magnetic Resonance Imaging can produce detailed images of the anatomy and physiology of the human body that can assist doctors in diagnosing and treating pathologies such as tumours.
