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Deep Learning per rilevare la Polmonite da immagini a Raggi X. Questo algoritmo identifica automaticamente se un paziente soffre o meno di polmonite osservando le radiografie del torace. Visto che sono in gioco le vite delle persone, questo algoritmo deve essere estremamente accurato.
Comprehensive Performance Analysis of Three Pretrained Transformer Models (ViT, Swin, and MaxViT) on ImageNet and Fine-tuned on the NIH Chest X-rays Dataset for Classifying 14 Chest Radiograph Pathologies
The notebook demonstrates the workflow for obtaining pore size distribution from binarized micro-CT images. The general principle involves identifying each pore, estimating the volume of each pore, and ultimately determining the radius of a sphere with an equivalent volume of each pore.
Бинарная классификация рентгеновских снимков грудной клетки. Определение наличия пневмонии у пациентов при помощи различных CNN архитектур. Использование метода Transfer Learning