A deep learning based dual encoder–decoder framework for anatomical structure segmentation in chest X-ray images

• Published in: Scientific reports Vol. 13; no. 1; pp. 791 - 14
• Main Authors: Ullah, Ihsan, Ali, Farman, Shah, Babar, El-Sappagh, Shaker, Abuhmed, Tamer, Park, Sang Hyun
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 16.01.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/1305; 631/114/1564; Chest; Deep Learning; Fluoroscopy; Humanities and Social Sciences; Humans; Image processing; Image Processing, Computer-Assisted - methods; multidisciplinary; Neural networks; Neural Networks, Computer; Pacemakers; Science; Science (multidisciplinary); Segmentation; Thorax - diagnostic imaging; X-Rays

Automated multi-organ segmentation plays an essential part in the computer-aided diagnostic (CAD) of chest X-ray fluoroscopy. However, developing a CAD system for the anatomical structure segmentation remains challenging due to several indistinct structures, variations in the anatomical structure sh...