AIMC Topic: Neural Networks, Computer

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Multiclassification of Endoscopic Colonoscopy Images Based on Deep Transfer Learning.

Computational and mathematical methods in medicine
With the continuous improvement of human living standards, dietary habits are constantly changing, which brings various bowel problems. Among them, the morbidity and mortality rates of colorectal cancer have maintained a significant upward trend. In ...

Self-Supervised Feature Learning and Phenotyping for Assessing Age-Related Macular Degeneration Using Retinal Fundus Images.

Ophthalmology. Retina
OBJECTIVE: Diseases such as age-related macular degeneration (AMD) are classified based on human rubrics that are prone to bias. Supervised neural networks trained using human-generated labels require labor-intensive annotations and are restricted to...

Convolutional neural networks for cytoarchitectonic brain mapping at large scale.

NeuroImage
Human brain atlases provide spatial reference systems for data characterizing brain organization at different levels, coming from different brains. Cytoarchitecture is a basic principle of the microstructural organization of the brain, as regional di...

Within node connectivity changes, not simply edge changes, influence graph theory measures in functional connectivity studies of the brain.

NeuroImage
Interest in understanding the organization of the brain has led to the application of graph theory methods across a wide array of functional connectivity studies. The fundamental basis of a graph is the node. Recent work has shown that functional nod...

A deep look into radiomics.

La Radiologia medica
Radiomics is a process that allows the extraction and analysis of quantitative data from medical images. It is an evolving field of research with many potential applications in medical imaging. The purpose of this review is to offer a deep look into ...

Accurate diagnosis of lung tissues for 2D Raman spectrogram by deep learning based on short-time Fourier transform.

Analytica chimica acta
Multivariate statistical analysis methods have an important role in spectrochemical analyses to rapidly identify and diagnose cancer and the subtype. However, utilizing these methods to analyze lager amount spectral data is challenging, and poses a m...

Evaluation of Open-Source and Pre-Trained Deep Convolutional Neural Networks Suitable for Player Detection and Motion Analysis in Squash.

Sensors (Basel, Switzerland)
In sport science, athlete tracking and motion analysis are essential for monitoring and optimizing training programs, with the goal of increasing success in competition and preventing injury. At present, contact-free, camera-based, multi-athlete dete...

General Purpose Low-Level Reinforcement Learning Control for Multi-Axis Rotor Aerial Vehicles.

Sensors (Basel, Switzerland)
This paper proposes a multipurpose reinforcement learning based low-level multirotor unmanned aerial vehicles control structure constructed using neural networks with model-free training. Other low-level reinforcement learning controllers developed i...

Esophagus Segmentation in CT Images via Spatial Attention Network and STAPLE Algorithm.

Sensors (Basel, Switzerland)
One essential step in radiotherapy treatment planning is the organ at risk of segmentation in Computed Tomography (CT). Many recent studies have focused on several organs such as the lung, heart, esophagus, trachea, liver, aorta, kidney, and prostate...