A non-invasive diagnostic approach for neuroblastoma utilizing preoperative enhanced computed tomography and deep learning techniques.

ABSTRACT: Neuroblastoma presents a wide variety of clinical phenotypes, demonstrating different levels of benignity and malignancy among its subtypes. Early diagnosis is essential for effective patient management. Computed tomography (CT) serves as a significant diagnostic tool for neuroblastoma, utilizing machine vision imaging, which offers advantages over traditional X-ray and ultrasound imaging modalities. However, the high degree of similarity among neuroblastoma subtypes complicates the diagnostic process. In response to these challenges, this study presents a modified version of the You Only Look Once (YOLO) algorithm, called YOLOv8-IE. This revised approach integrates feature fusion and inverse residual attention mechanisms. The aim of YOLO-IE is to improve the detection and classification o

SUBMITTER: Wang Y 

PROVIDER: S-EPMC12033241 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature