AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 7591 to 7600 of 10288 articles

Fully automatic liver attenuation estimation combing CNN segmentation and morphological operations.

Medical physics
PURPOSE: Manually tracing regions of interest (ROIs) within the liver is the de facto standard method for measuring liver attenuation on computed tomography (CT) in diagnosing nonalcoholic fatty liver disease (NAFLD). However, manual tracing is resou...

Local Interpretable Model-Agnostic Explanations for Classification of Lymph Node Metastases.

Sensors (Basel, Switzerland)
An application of explainable artificial intelligence on medical data is presented. There is an increasing demand in machine learning literature for such explainable models in health-related applications. This work aims to generate explanations on ho...

Quantitative and Qualitative Evaluation of Convolutional Neural Networks with a Deeper U-Net for Sparse-View Computed Tomography Reconstruction.

Academic radiology
RATIONALE AND OBJECTIVES: To evaluate the utility of a convolutional neural network (CNN) with an increased number of contracting and expanding paths of U-net for sparse-view CT reconstruction.

Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD.

Magnetic resonance in medicine
PURPOSE: To apply an artificial neural network (ANN) for fast and robust quantification of the oxygen extraction fraction (OEF) from a combined QSM and quantitative BOLD analysis of gradient echo data and to compare the ANN to a traditional quasi-New...

StomataCounter: a neural network for automatic stomata identification and counting.

The New phytologist
Stomata regulate important physiological processes in plants and are often phenotyped by researchers in diverse fields of plant biology. Currently, there are no user-friendly, fully automated methods to perform the task of identifying and counting st...

Computer Vision Classification of Barley Flour Based on Spatial Pyramid Partition Ensemble.

Sensors (Basel, Switzerland)
Imaging sensors are largely employed in the food processing industry for quality control. Flour from malting barley varieties is a valuable ingredient in the food industry, but its use is restricted due to quality aspects such as color variations and...

Deep learning-enabled accurate normalization of reconstruction kernel effects on emphysema quantification in low-dose CT.

Physics in medicine and biology
Lung densitometry is being frequently adopted in CT-based emphysema quantification, yet known to be affected by the choice of reconstruction kernel. This study presents a two-step deep learning architecture that enables accurate normalization of reco...

An Improved Convolutional Neural Network Algorithm and Its Application in Multilabel Image Labeling.

Computational intelligence and neuroscience
In today's society, image resources are everywhere, and the number of available images can be overwhelming. Determining how to rapidly and effectively query, retrieve, and organize image information has become a popular research topic, and automatic ...

Neural Multimodal Cooperative Learning Toward Micro-Video Understanding.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The prevailing characteristics of micro-videos result in the less descriptive power of each modality. The micro-video representations, several pioneer efforts proposed, are limited in implicitly exploring the consistency between different modality in...

Novel adversarial semantic structure deep learning for MRI-guided attenuation correction in brain PET/MRI.

European journal of nuclear medicine and molecular imaging
OBJECTIVE: Quantitative PET/MR imaging is challenged by the accuracy of synthetic CT (sCT) generation from MR images. Deep learning-based algorithms have recently gained momentum for a number of medical image analysis applications. In this work, a no...