AIMC Topic: Image Processing, Computer-Assisted

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Resolution-dependent MRI-to-CT translation for orthotopic breast cancer models using deep learning.

Physics in medicine and biology
This study aims to investigate the feasibility of utilizing generative adversarial networks (GANs) to synthesize high-fidelity computed tomography (CT) images from lower-resolution MR images. The goal is to reduce patient exposure to ionizing radiati...

A hybrid network for fiber orientation distribution reconstruction employing multi-scale information.

Medical physics
BACKGROUND: Accurate fiber orientation distribution (FOD) is crucial for resolving complex neural fiber structures. However, existing reconstruction methods often fail to integrate both global and local FOD information, as well as the directional inf...

A Multi-task learning U-Net model for end-to-end HEp-2 cell image analysis.

Artificial intelligence in medicine
Antinuclear Antibody (ANA) testing is pivotal to help diagnose patients with a suspected autoimmune disease. The Indirect Immunofluorescence (IIF) microscopy performed with human epithelial type 2 (HEp-2) cells as the substrate is the reference metho...

A Near-Infrared Imaging System for Robotic Venous Blood Collection.

Sensors (Basel, Switzerland)
Venous blood collection is a widely used medical diagnostic technique, and with rapid advancements in robotics, robotic venous blood collection has the potential to replace traditional manual methods. The success of this robotic approach is heavily d...

A systematic review on feature extraction methods and deep learning models for detection of cancerous lung nodules at an early stage -the recent trends and challenges.

Biomedical physics & engineering express
Lung cancer is one of the most common life-threatening worldwide cancers affecting both the male and the female populations. The appearance of nodules in the scan image is an early indication of the development of cancer cells in the lung. The Low Do...

CIMIL-CRC: A clinically-informed multiple instance learning framework for patient-level colorectal cancer molecular subtypes classification from H&E stained images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Treatment approaches for colorectal cancer (CRC) are highly dependent on the molecular subtype, as immunotherapy has shown efficacy in cases with microsatellite instability (MSI) but is ineffective for the microsatellite sta...

Blip-up blip-down circular EPI (BUDA-cEPI) for distortion-free dMRI with rapid unrolled deep learning reconstruction.

Magnetic resonance imaging
PURPOSE: BUDA-cEPI has been shown to achieve high-quality, high-resolution diffusion magnetic resonance imaging (dMRI) with fast acquisition time, particularly when used in conjunction with S-LORAKS reconstruction. However, this comes at a cost of mo...

Automated Single Cell Phenotyping of Time-of-Flight Secondary Ion Mass Spectrometry Tissue Images.

Journal of the American Society for Mass Spectrometry
Existing analytical techniques are being improved or applied in new ways to profile the tissue microenvironment (TME) to better understand the role of cells in disease research. Fully understanding the complex interactions between cells of many diffe...

A Parkinson's disease-related nuclei segmentation network based on CNN-Transformer interleaved encoder with feature fusion.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automatic segmentation of Parkinson's disease (PD) related deep gray matter (DGM) nuclei based on brain magnetic resonance imaging (MRI) is significant in assisting the diagnosis of PD. However, due to the degenerative-induced changes in appearance, ...

Convolutional neural network for oral cancer detection combined with improved tunicate swarm algorithm to detect oral cancer.

Scientific reports
Early Diagnosis of oral cancer is very important and can save you from some oral malignancies. However, while this approach aids in the rapid healing of patients and the preservation of their lives, there are several causes for poor and wrong diagnos...