OBJECTIVES: Current dental CBCT segmentation tools often lack accuracy, accessibility, or comprehensive anatomical coverage. To address this, we constructed a densely annotated dental CBCT dataset and developed a deep learning model, OraSeg, for toot...
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Sep 25, 2025
This paper examines the current challenges in computed tomography (CT), with a critical exploration of existing methodologies from a mathematical perspective. Specifically, it aims to identify research directions to enhance image quality in low-dose,...
Although recent advances in CNNs and Transformers have significantly improved medical image segmentation, these models often struggle to balance segmentation accuracy, inference speed, and architectural simplicity. Lightweight MLP-based methods have ...
Imaging technologies and staining based pathology are important components of common practice cancer care. Specifically, H&E imaging is standard for almost all cancer patients. Traditionally, H&E images can serve, when used by experienced trained pat...
The identification of various objects and species found in nature is of great importance today. Active and passive imaging systems are in a beneficial position in this direction, both in terms of cost and convenience. Recently, mucilage events in our...
BACKGROUND: Circulating tumor cells (CTCs) in peripheral blood are crucial for prognosis, treatment response, disease monitoring, and personalized therapy. However, identifying CTCs remains challenging due to their scarcity and heterogeneity, even wi...
The classification and identification of forest tree species is of great value in the study of species diversity and forest monitoring. With the development of emerging technologies, the combination of remote sensing images and deep learning methods ...
Alzheimer's disease (AD) is a progressive illness that can cause behavioural abnormalities, personality changes, and memory loss. Early detection helps with future planning for both the affected person and caregivers. Thus, an innovative hybrid Deep ...
Pathological images are prone to artifacts during scanning and preparation, which can compromise diagnostic accuracy. Therefore, robust artifact detection is essential for improving image quality and ensuring reliable pathological assessments. Howeve...
With the rapid advancement of computer vision technology, traditional manual methods of reading meters are increasingly being replaced by automated water meter reading technologies based on image recognition. This technology can precisely locate and ...
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