A Lightweight, Rapid and Efficient Deep Convolutional Network for Chest X-Ray Tuberculosis Detection-Reference-Cited by-同舟云学术

A Lightweight, Rapid and Efficient Deep Convolutional Network for Chest X-Ray Tuberculosis Detection

Published:2023-04-18 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)
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Author:

Capellán-Martín Daniel¹,Gómez-Valverde Juan J.¹,Bermejo-Peláez David¹,Ledesma-Carbayo María J.¹

Affiliation:

1. Universidad Politécnica de Madrid,Biomedical Image Technologies, ETSI Telecomunicación

Funder

Universidad Politécnica de Madrid

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10230311/10230322/10230500.pdf?arnumber=10230500

Reference18 articles.

1. TB-Net: A Tailored, Self-Attention Deep Convolutional Neural Network Design for Detection of Tuberculosis Cases From Chest X-Ray Images

2. CheX-aid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV;rajpurkar;NPJ Digital Medicine 2020 3 1,2020

3. Contrast Limited Adaptive Histogram Equalization

4. Two public chest X-ray datasets for computer-aided screening of pulmonary diseases;jaeger;Quant Imaging Med Surg,2014

5. Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization

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