AIMC Topic: Deep Learning

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Partial-ring PET image restoration using a deep learning based method.

Physics in medicine and biology
PET scanners with partial-ring geometry have been proposed for various imaging purposes. The incomplete projection data obtained from this design cause undesirable artifacts in the reconstructed images. In this study, we investigated the performance ...

Deep Learning with Taxonomic Loss for Plant Identification.

Computational intelligence and neuroscience
Plant identification is a fine-grained classification task which aims to identify the family, genus, and species according to plant appearance features. Inspired by the hierarchical structure of taxonomic tree, the taxonomic loss was proposed, which ...

Celiac disease diagnosis from videocapsule endoscopy images with residual learning and deep feature extraction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Videocapsule endoscopy (VCE) is a relatively new technique for evaluating the presence of villous atrophy in celiac disease patients. The diagnostic analysis of video frames is currently time-consuming and tedious. Recently,...

Spine Explorer: a deep learning based fully automated program for efficient and reliable quantifications of the vertebrae and discs on sagittal lumbar spine MR images.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Although quantitative measurements improve the assessment of disc degeneration, acquirement of quantitative measurements relies on manual segmentation on lumbar magnetic resonance images (MRIs), which may introduce subjective bias...

Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps.

Medical image analysis
Colorectal polyps are known to be potential precursors to colorectal cancer, which is one of the leading causes of cancer-related deaths on a global scale. Early detection and prevention of colorectal cancer is primarily enabled through manual screen...

Towards near real-time assessment of surgical skills: A comparison of feature extraction techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Surgical skill assessment aims to objectively evaluate and provide constructive feedback for trainee surgeons. Conventional methods require direct observation with assessment from surgical experts which are both unscalable a...

Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning.

Radiology
Background Deep learning (DL) algorithms are gaining extensive attention for their excellent performance in image recognition tasks. DL models can automatically make a quantitative assessment of complex medical image characteristics and achieve incre...

Deep learning modeling using normal mammograms for predicting breast cancer risk.

Medical physics
PURPOSE: To investigate two deep learning-based modeling schemes for predicting short-term risk of developing breast cancer using prior normal screening digital mammograms in a case-control setting.

Distributed deep learning across multisite datasets for generalized CT hemorrhage segmentation.

Medical physics
PURPOSE: As deep neural networks achieve more success in the wide field of computer vision, greater emphasis is being placed on the generalizations of these models for production deployment. With sufficiently large training datasets, models can typic...