Recently, the field of generative models has seen a significant advancement with the
introduction of Diffusion Probabilistic Models (DPMs). The Denoising Diffusion Implicit Model …

Weakly supervised object localization (WSOL) is one of the most popular and challenging
tasks in computer vision. This task is to localize the objects in the images given only the …

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 …

Rib fractures are a common and potentially severe injury that can be challenging and labor-
intensive to detect in CT scans. While there have been efforts to address this field, the lack of …

Existing pulmonary nodule detection methods often train models in a fully-supervised setting
that requires strong labels (ie, bounding box labels) as label information. However, manual …

Lung cancer stands as the leading cause of cancer related mortality worldwide. Precise and
automated identification of lung nodules through 3D Computed Tomography (CT) scans is …

Cross domain pulmonary nodule detection suffers from performance degradation due to
large shift of data distributions between the source and target domain. Besides, considering …

Thoracic computed tomography (CT) currently plays the primary role in pulmonary nodule
detection, where the reconstruction kernel significantly impacts performance in computer …

Computer-aided diagnosis (CAD) systems play vital roles in the early detection of pulmonary
nodules for reducing lung cancer mortality rates. To provide better services for professional …

Globally, lung cancer ranks as the primary reason for fatalities associated with cancer.
Accurate detection of pulmonary nodules in computed tomography (CT) images is crucial for …