AIMC Topic: Image Processing, Computer-Assisted

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Optimization of sparse-view CT reconstruction based on convolutional neural network.

Medical physics
BACKGROUND: Sparse-view CT shortens scan time and reduces radiation dose but results in severe streak artifacts due to insufficient sampling data. Deep learning methods can now suppress these artifacts and improve image quality in sparse-view CT reco...

Development and validation of fully automated robust deep learning models for multi-organ segmentation from whole-body CT images.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: This study aimed to develop a deep-learning framework to generate multi-organ masks from CT images in adult and pediatric patients.

Pan-sharpening via Symmetric Multi-Scale Correction-Enhancement Transformers.

Neural networks : the official journal of the International Neural Network Society
Pan-sharpening is a widely employed technique for enhancing the quality and accuracy of remote sensing images, particularly in high-resolution image downstream tasks. However, existing deep-learning methods often neglect the self-similarity in remote...

DLPVI: Deep learning framework integrating projection, view-by-view backprojection, and image domains for high- and ultra-sparse-view CBCT reconstruction.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This study proposes a deep learning framework, DLPVI, which integrates projection, view-by-view backprojection (VVBP), and image domains to improve the quality of high-sparse-view and ultra-sparse-view cone-beam computed tomography (CBCT) images. The...

Meta-learning guidance for robust medical image synthesis: Addressing the real-world misalignment and corruptions.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Deep learning-based image synthesis for medical imaging is currently an active research topic with various clinically relevant applications. Recently, methods allowing training with misaligned data have started to emerge, yet current solution lack ro...

Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging.

NeuroImage
INTRODUCTION: Altered neurometabolism is an important pathological mechanism in many neurological diseases and brain cancer, which can be mapped non-invasively by Magnetic Resonance Spectroscopic Imaging (MRSI). Advanced MRSI using non-cartesian comp...

Detecting living microalgae in ship ballast water based on stained microscopic images and deep learning.

Marine pollution bulletin
Motivated by the need of rapid detection of living microalgae cells in ship ballast water, this study is intended to determine the activities of microalgae using stained microscopic images and detect the living cells with image processing algorithms....

Deep learning initialized compressed sensing (Deli-CS) in volumetric spatio-temporal subspace reconstruction.

Magma (New York, N.Y.)
OBJECT: Spatio-temporal MRI methods offer rapid whole-brain multi-parametric mapping, yet they are often hindered by prolonged reconstruction times or prohibitively burdensome hardware requirements. The aim of this project is to reduce reconstruction...

Artificial Intelligence in IR Thermal Imaging and Sensing for Medical Applications.

Sensors (Basel, Switzerland)
The state of the art in IR thermal imaging methods for applications in medical diagnostics is discussed. A review of advances in IR thermal imaging technology in the years 1960-2024 is presented. Recently used artificial intelligence (AI) methods in ...

A continuous-action deep reinforcement learning-based agent for coronary artery centerline extraction in coronary CT angiography images.

Medical & biological engineering & computing
The lumen centerline of the coronary artery allows vessel reconstruction used to detect stenoses and plaques. Discrete-action-based centerline extraction methods suffer from artifacts and plaques. This study aimed to develop a continuous-action-based...