The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …

The comprehensive integration of machine learning healthcare models within clinical
practice remains suboptimal, notwithstanding the proliferation of high-performing solutions …

The task of multimodal cancer detection is to determine the locations and categories of
lesions by using different imaging techniques, which is one of the key research methods for …

Aiming at detecting COVID-19 effectively, a multiscale class residual attention (MCRA)
network is proposed via chest X-ray (CXR) image classification. First, to overcome the data …

Pixel-level prediction of early lesions is important for disease treatment and saving patients'
lives. Owing to the heterogeneity of pathological brain structures and the complexity of brain …

Reliable localization of lymph nodes (LNs) in multi-parametric MRI (mpMRI) studies plays a
major role in the assessment of lymphadenopathy and staging of metastatic disease …

Accurate and automatic detection of tiny lesions in medical imaging plays a critical role in
comprehensive cancer diagnosis, staging, treatment, follow-up, and prognosis. Numerous …

Detection of abnormalities within the inner ear is a challenging task even for experienced
clinicians. In this study, we propose an automated method for automatic abnormality …

Accurate and automatic detection of pelvic lymph nodes in computed tomography (CT)
scans is critical for diagnosing lymph node metastasis in colorectal cancer, which in turn …

Abstract Purpose Lymph nodes (LNs) in the chest have a tendency to enlarge due to various
pathologies, such as lung cancer or pneumonia. Clinicians routinely measure nodal size to …