Classification of chest pneumonia from x-ray images using new architecture based on ResNet
TALIBI ALAOUI Youssef, BERRAHOU Aissam, Khalid Douge, Imane Belabed, Jaara El Miloud
Abstract
Pneumonia is a potentially fatal bacterial or viral lung infection. The detection of pneumonia anomalies in the early lungs, can save the life of a child or an old lady, especially, in the early moments;These divergences have a very minimal size.In this paper we propose a new architecture based on ResNet 50, we project the adjusted Resnet50 model, based on medical images of the chest to bring out the infected examples with pneumonia. The result predicted are very interesting (97, 65 %) by comparing them with several prior scientific researches and radiologists hope.
Topics & Concepts
PneumoniaArchitectureResidual neural networkLungMedicineComputer scienceComputed tomographyRadiologyArtificial intelligenceInternal medicineDeep learningHistoryArchaeologyCOVID-19 diagnosis using AIRadiomics and Machine Learning in Medical ImagingAI in cancer detection