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A novel deep learning-based pipeline architecture for pulp stone detection on panoramic radiographs.
Oral Radiol
January 2025
Department of Software Engineering, Faculty of Engineering, Muğla Sıtkı Koçman University, Muğla, 4800, Turkey.
Objectives: Pulp stones are ectopic calcifications located in pulp tissue. The aim of this study is to introduce a novel method for detecting pulp stones on panoramic radiography images using a deep learning-based two-stage pipeline architecture.
Materials And Methods: The first stage involved tooth localization with the YOLOv8 model, followed by pulp stone classification using ResNeXt.
Microscopic augmented reality calibration with contactless line-structured light registration for surgical navigation.
Med Biol Eng Comput
January 2025
Mechanical Engineering Department, Tianjin University, No. 135, Yaguan Road, Haihe Education Park, Jinnan District, Tianjin City, 300350, China.
The use of AR technology in image-guided neurosurgery enables visualization of lesions that are concealed deep within the brain. Accurate AR registration is required to precisely match virtual lesions with anatomical structures displayed under a microscope. The purpose of this work was to develop a real-time augmented surgical navigation system using contactless line-structured light registration, microscope calibration, and visible optical tracking.
View Article and Find Full Text PDFOver-resection, or under-resection, of the femoral cam lesion in patients having hip arthroscopy for femoroacetabular impingement syndrome indicate different possible solutions.
Arthroscopy
January 2025
Kansas City Orthopedic Alliance, 10777 Nall Avenue, Overland Park, KS 66224. Electronic address:
As surgeons, we strive to recognize and correct any mistakes that may occur before completing an operation, and importantly, do our best to avoid irreversible mistakes. Over-resection of the femoral cam lesion in patients having hip arthroscopy for femoroacetabular impingement syndrome has been considered irreversible. While cam under-resection is a technical complication of femoroacetabular impingement surgery to be avoided, avoiding this at the expense of over-resection of the proximal femur is of great concern.
View Article and Find Full Text PDFUnveiling patterns in spatial transcriptomics data: a novel approach utilizing graph attention autoencoder and multiscale deep subspace clustering network.
Gigascience
January 2025
School of Computer Science, Hunan University of Technology, Zhuzhou 412007, Hunan, China.
Background: The accurate deciphering of spatial domains, along with the identification of differentially expressed genes and the inference of cellular trajectory based on spatial transcriptomic (ST) data, holds significant potential for enhancing our understanding of tissue organization and biological functions. However, most of spatial clustering methods can neither decipher complex structures in ST data nor entirely employ features embedded in different layers.
Results: This article introduces STMSGAL, a novel framework for analyzing ST data by incorporating graph attention autoencoder and multiscale deep subspace clustering.
Application of deep learning in automated localization and interpretation of coronary artery calcification in oncological PET/CT scans.
Int J Cardiovasc Imaging
January 2025
Artificial Intelligence Center, China Medical University Hospital, China Medical University, Taichung, Taiwan.
Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radiation exposure and the need for specialized personnel. This study aims to develop an artificial intelligence (AI) method to automatically detect CAC from non-gated, freely-breathing, low-dose CT images obtained from positron emission tomography/computed tomography scans.
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