Birth complications, particularly jaundice, are one of the leading causes of adolescent death and disease all over the globe. The main severity of these illnesses may diminish if scholars study more about their sources and progress toward effective t...
Brain tumor segmentation plays a crucial role in clinical diagnostics and treatment planning, yet accurate and efficient segmentation remains a significant challenge due to complex tumor structures and variations in imaging modalities. Multi-feature ...
Ultrasound imaging plays an important role in fetal growth and maternal-fetal health evaluation, but due to the complicated anatomy of the fetus and image quality fluctuation, its interpretation is quite challenging. Although deep learning include Co...
Nowadays, breast cancer is one of the leading causes of death among women. This highlights the need for precise X-ray image analysis in the medical and imaging fields. In this study, we present an advanced perceptual deep learning framework that extr...
Accurate identification of Oudemansiella raphanipes growth stages is crucial for understanding its development and optimizing cultivation. However, deep learning methods for this task remain unexplored. This paper introduces OR-FCOS, an enhanced full...
Epicardial Adipose Tissue (EAT) is a recognized risk factor for cardiovascular diseases and plays a pivotal role in the pathophysiology of Atrial Fibrillation (AF). Accurate automatic segmentation of the EAT around the Left Atrium (LA) from Magnetic ...
Molecular biostatistical workflows in oncology often rely on predictive models that use multimodal data. Advances in deep learning and artificial intelligence technologies have enabled the multimodal fusion of large volumes of multimodal data. Here, ...
In recent times, chronic kidney cancer has been considered a significant cause of cancer, and Renal Cell Carcinoma (RCC) has become a significant prevalent among various kidney cancer conditions. The analysis of kidney cancer, an important and often ...
In complex geological environments, the morphology, orientation and distribution characteristics of cracks in the rock directly affect the stability assessment for rock masses and engineering safety decisions. However, the traditional manual interpre...
Semantic segmentation of medical images is pivotal in applications like disease diagnosis and treatment planning. While deep learning automates this task effectively, it struggles in ultra low-data regimes for the scarcity of annotated segmentation m...
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