Graph Neural Networks for Digital Pathology by Vincenzo DELLA MEA, Hafsa AKEBLI, Kevin ROITERO

“…GNNs are well-suited for analyzing data such as social networks, molecular structures, and medical images, capturing both local and global patterns. …”
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Deep Learning Image Classification Rontgen Dada pada Kasus Covid-19 Menggunakan Algoritma Convolutional Neural Network by Leni Anggraini Susanti, Agus Mohamad Soleh, Bagus Sartono

“…Abstract This research proposes using a Convolutional Neural Network (CNN) with VGGNet-19 and ResNet-50 architectures for COVID-19 diagnosis through chest X-ray image analysis. …”
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Leveraging commonality across multiple tissue slices for enhanced whole slide image classification using graph convolutional networks by Sakonporn Noree, Willmer Rafell Quinones Robles, Young Sin Ko, Mun Yong Yi

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Improving the quality of SAR radar image detection and identification using neural network to increase the security factor of military tactics by ali alizade, Jalil Mazloum, behrang hadian, ahmad dolatkhah, behnam dorostkar

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A two-stage CNN model for the classification and severity analysis of retinal and choroidal diseases in OCT images by Neetha George, Linu Shine, Ambily N, Bejoy Abraham, Sivakumar Ramachandran

“…In this article, a two-stage classification model using convolutional neural network (CNN) is proposed for the classification and severity analysis of retinal and choroidal diseases in optical coherence tomography (OCT) images. …”
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Deep learning analysis of fMRI data for predicting Alzheimer's Disease: A focus on convolutional neural networks and model interpretability. by Xiao Zhou, Sanchita Kedia, Ran Meng, Mark Gerstein

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Real-Time Detection of Meningiomas by Image Segmentation: A Very Deep Transfer Learning Convolutional Neural Network Approach by Debasmita Das, Chayna Sarkar, Biswadeep Das

“…All the hidden layers in our VGG network also use ReLU. A dataset consisting of 264 3D FLAIR sMRI image segments from three different classes (meningioma, tuberculoma, and normal) was employed. …”
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Dataset for training neural networks in concrete crack detection: laboratory-classified beam and column imagesRepositorio Institucional – Universidad de Lima by Alexandre Almeida Del Savio, Ana Luna Torres, Daniel Cárdenas-Salas, Mónica Vergara Olivera, Gianella Urday Ibarra

“…The dataset includes five object classes representing distinct cracks and failures in beams and columns and corresponding.txt files containing classification and coordinates data. This dataset is designed to facilitate developing and validating of neural network-based computer vision models for automated crack detection. …”
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Exploring Solar Granulation: from IMaX/SUNRISE to DKIST by Reza Mansouri, Rafal Angryk, Kevin Reardon

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Analysis of Deep Learning Techniques for Vehicle Detection and Reidentification Using Data from Multiple Drones and Public Datasets by FELIPE P.A. EUPHRÁSIO, RAFAEL M. DE ANDRADE, ELCIO H. SHIGUEMORI, LIANGRID L. SILVA, MOISÉS JOSÉ S. FREITAS, NATHAN AUGUSTO Z. XAVIER, ARGEMIRO S.S. SOBRINHO

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Mapping Coastal Soil Salinity and Vegetation Dynamics Using Sentinel-1 and Sentinel-2 Data Fusion With Machine Learning Techniques by Wen Liu, Tiezhu Shi, Zhinian Zhao, Chao Yang

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Neural network for step anomaly detection in head motion during fMRI using meta-learning adaptation by N.S. Davydov, V.V. Evdokimova, P.G. Serafimovich, V.I. Protsenko, A.G. Khramov, A.V. Nikonorov

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Towards ROXAS AI: automatic multi-species ring boundaries segmentation as regression in anatomical images by Marc Katzenmaier, Marc Katzenmaier, Vivien Sainte Fare Garnot, Jan Dirk Wegner, Georg von Arx, Georg von Arx

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Different rs-fMRI Data Processing Methods in the Study of Vascular Cognitive Impairment by Ying GUAN, Luwen ZHU, Feng WANG, Danna CAO, Xiaoling LI, Qiang TANG

“…Different data processing methods have different meanings, advantages and disadvantages, and application value, and different data processing and analysis methods have some differences in the results, such as ALFF and ReHo, which belong to the analysis method of local functional activity characteristics; functional connectivity and brain network belong to linear correlation analysis method. …”
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Automatic Blob Detection Method for Cancerous Lesions in Unsupervised Breast Histology Images by Vincent Majanga, Ernest Mnkandla, Zenghui Wang, Donatien Koulla Moulla

“…The early detection of cancerous lesions is a challenging task given the cancer biology and the variability in tissue characteristics, thus rendering medical image analysis tedious and time-inefficient. In the past, conventional computer-aided diagnosis (CAD) and detection methods have heavily relied on the visual inspection of medical images, which is ineffective, particularly for large and visible cancerous lesions in such images. …”
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Resting-state brain network analysis and applied evaluation of global developmental delay in preterm infants: A functional near-infrared spectroscopic study by Hengye Huang, Karol Kexin Sun, Dan Wu, Chuncao Zhang, Yanyan Huo, Yuan Tian, Guangjun Yu

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Development of an AI-Based Image Analysis Model for Verifying Partial Defects in Nuclear Fuel Assemblies by Seulah Kim, Dayun Park, Hyung-Joo Choi, Chulhee Min, Jaejoon Ahn

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Morphometric differences between basal cell carcinomas & melanomas of the head & neck versus other sites and their influence on neural networks by Jonas Hue, Jinendra Ekanayake, Jamshid Dehmeshki, Jagtar Dhanda

“…Objective: We aimed to investigate the morphometric differences between anatomic sites of the head and neck(H&N) versus other body sites in basal cell carcinomas and melanomas and how these differences may impact neural network model accuracy. Methods: Morphometric image analysis of the BCCs(n=422) and melanomas(n=868) from the publicly available HAM10000 dataset was performed using an open-source image analysis software. …”
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PRIVACY-AWARE MALARIA DETECTION: U-NET MODEL WITH K-ANONYMITY FOR CONFIDENTIAL IMAGE ANALYSIS by Ghazala Hcini, Imen Jdey

“…These results highlight the effectiveness of integrating privacy-preserving techniques with advanced neural network architectures, improving both security and performance in diverse image analysis applications. …”
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Multimodal learning for enhanced SPECT/CT imaging in sports injury diagnosis by Zhengzheng Jiang, YaWen Shen

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