AIMC Topic: Image Processing, Computer-Assisted

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Convolutional Neural Network Ensemble Segmentation With Ratio-Based Sampling for the Arteries and Veins in Abdominal CT Scans.

IEEE transactions on bio-medical engineering
OBJECTIVE: Three-dimensional (3D) blood vessel structure information is important for diagnosis and treatment in various clinical scenarios. We present a fully automatic method for the extraction and differentiation of the arterial and venous vessel ...

Deep learning in structural and functional lung image analysis.

The British journal of radiology
The recent resurgence of deep learning (DL) has dramatically influenced the medical imaging field. Medical image analysis applications have been at the forefront of DL research efforts applied to multiple diseases and organs, including those of the l...

Cryo-balloon catheter localization in X-Ray fluoroscopy using U-net.

International journal of computer assisted radiology and surgery
PURPOSE: Automatic identification of interventional devices in X-ray (XR) fluoroscopy offers the potential of improved navigation during transcatheter endovascular procedures. This paper presents a prototype implementation of fully automatic 3D recon...

Diverse data augmentation for learning image segmentation with cross-modality annotations.

Medical image analysis
The dearth of annotated data is a major hurdle in building reliable image segmentation models. Manual annotation of medical images is tedious, time-consuming, and significantly variable across imaging modalities. The need for annotation can be amelio...

A Machine Vision Approach for Bioreactor Foam Sensing.

SLAS technology
Machine vision is a powerful technology that has become increasingly popular and accurate during the last decade due to rapid advances in the field of machine learning. The majority of machine vision applications are currently found in consumer elect...

Block-cyclic stochastic coordinate descent for deep neural networks.

Neural networks : the official journal of the International Neural Network Society
We present a stochastic first-order optimization algorithm, named block-cyclic stochastic coordinate descent (BCSC), that adds a cyclic constraint to stochastic block-coordinate descent in the selection of both data and parameters. It uses different ...

Three ways of knowing: the integration of clinical expertise, evidence-based medicine, and artificial intelligence in assisted reproductive technologies.

Journal of assisted reproduction and genetics
Decision-making in fertility care is on the cusp of a significant frameshift. Online tools to integrate artificial intelligence into the decision-making process across all aspects of ART are rapidly emerging. These tools have the potential to improve...

Artificial Intelligence-based methods in head and neck cancer diagnosis: an overview.

British journal of cancer
BACKGROUND: This paper reviews recent literature employing Artificial Intelligence/Machine Learning (AI/ML) methods for diagnostic evaluation of head and neck cancers (HNC) using automated image analysis.

Geometric deep learning enables 3D kinematic profiling across species and environments.

Nature methods
Comprehensive descriptions of animal behavior require precise three-dimensional (3D) measurements of whole-body movements. Although two-dimensional approaches can track visible landmarks in restrictive environments, performance drops in freely moving...

Learning dual-margin model for visual tracking.

Neural networks : the official journal of the International Neural Network Society
Existing trackers usually exploit robust features or online updating mechanisms to deal with target variations which is a key challenge in visual tracking. However, the features being robust to variations remain little spatial information, and existi...