AIMC Topic: Image Processing, Computer-Assisted

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Semi-supervised motion flow and myocardial strain estimation in cardiac videos using distance maps and memory networks.

Computers in biology and medicine
Myocardial strain plays a crucial role in diagnosing heart failure and myocardial infarction. Its computation relies on assessing heart muscle motion throughout the cardiac cycle. This assessment can be performed by following key points on each frame...

ASD-GraphNet: A novel graph learning approach for Autism Spectrum Disorder diagnosis using fMRI data.

Computers in biology and medicine
Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition with heterogeneous symptomatology, making accurate diagnosis challenging. Traditional methods rely on subjective behavioral assessments, often overlooking subtle neural biomarke...

Efficient Compression of Mass Spectrometry Images via Contrastive Learning-Based Encoding.

Analytical chemistry
In this study, we introduce a novel encoding algorithm utilizing contrastive learning to address the substantial data size challenges inherent in mass spectrometry imaging. Our algorithm compresses MSI data into fixed-length vectors, significantly re...

ViT-GCN: a novel hybrid model for accurate pneumonia diagnosis from x-ray images.

Biomedical physics & engineering express
This study aims to enhance the accuracy of pneumonia diagnosis from x-ray images by developing a model that integrates Vision Transformer (ViT) and Graph Convolutional Networks (GCN) for improved feature extraction and diagnostic performance. The ViT...

Efficient wheat variety identification using Raman hyperspectral imaging in combination with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Wheat (Triticum aestivum L.) is recognized as a globally important staple crop, with its varietal differences influencing food processing, nutritional value, and agricultural productivity. Traditional identification methods are often considered ineff...

Computer vision to predict cell seeding coverage in re-endothelialized mouse lungs.

Scientific reports
Transplantation of donor grafts recellularized with recipient-derived or non-immunogenic universal cells is a potential means of reducing the graft rejection and post-transplant complications in lung transplantation. Achieving a fully recellularized ...

Enhancing cardiac disease detection via a fusion of machine learning and medical imaging.

Scientific reports
Cardiovascular illnesses continue to be a predominant cause of mortality globally, underscoring the necessity for prompt and precise diagnosis to mitigate consequences and healthcare expenditures. This work presents a complete hybrid methodology that...

Enhancing breast cancer classification using a deep sparse wavelet autoencoder approach.

Scientific reports
As digital imaging technology advances, accurate classification of 2D breast cancer images becomes increasingly crucial for early detection and staging. This paper introduces a novel classification approach that integrates deep learning, sparse codin...

Video-based pupillometry using Fourier Mellin image correlation.

Scientific reports
We introduce a novel method for evaluating the pupil light reflex (PLR) response using digital video recordings. Expensive, specialized devices are replacing traditional penlight tests in emergency and neurotrauma departments, but they are not widely...

Image-based inference of tumor cell trajectories enables large-scale cancer progression analysis.

Science advances
Current approaches to estimating cell trajectories, tumor progression dynamics, and cell population diversity of tumor microenvironment often depend on single-cell RNA sequencing, which is costly and resource intensive. To address this limitation, we...