A major challenge in biophotonics is multimodal imaging to obtain both morphological and molecular information at depth. We demonstrate a hybrid approach integrating optical coherence tomography (OCT) with wavelength modulated spatially offset Raman spectroscopy (WM-SORS). With depth colocalization obtained from the OCT, we can penetrate 1.2-mm deep into strong scattering media (lard) to acquire up to a 14-fold enhancement of a Raman signal from a hidden target (polystyrene) with a spatial offset. Our approach is capable of detecting both Raman and OCT signals for pharmaceutical particles embedded in turbid media and revealing the white matter at depth within a 0.6-mm thick brain tissue layer. This depth resolved label-free multimodal approach is a powerful route to analyze complex biomedical samples.
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http://dx.doi.org/10.1002/jbio.201700129 | DOI Listing |
Arch Gynecol Obstet
January 2025
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Road, Nanning, 530021, Guangxi, China.
Purpose: This case report aims to present a rare case of endometrial carcinosarcoma, a highly malignant tumor with a poor prognosis. The primary objective is to describe this unique case's clinical presentation, multimodal magnetic resonance imaging (MRI) features, typical histopathological characteristics and surgical treatment.
Methods: A detailed analysis of the patient's medical history, preoperative imaging evaluation, and treatment approach was conducted.
J Clin Med
December 2024
Lions Eye Institute, Perth, WA 6009, Australia.
Diabetic macular edema (DME) is a significant cause of vision loss. The development of peripheral non-perfusion (PNP) might be associated with the natural course, severity, and treatment of DME. The present study seeks to understand the predictive power of central macular changes and clinico-demographic features for PNP in patients with clinically significant DME.
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January 2025
Faculty of Science and Technology, Keio University, Yokohama 223-8522, Japan.
Person identification is a critical task in applications such as security and surveillance, requiring reliable systems that perform robustly under diverse conditions. This study evaluates the Vision Transformer (ViT) and ResNet34 models across three modalities-RGB, thermal, and depth-using datasets collected with infrared array sensors and LiDAR sensors in controlled scenarios and varying resolutions (16 × 12 to 640 × 480) to explore their effectiveness in person identification. Preprocessing techniques, including YOLO-based cropping, were employed to improve subject isolation.
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December 2024
School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.
Megavoltage computed tomography (MVCT) plays a crucial role in patient positioning and dose reconstruction during tomotherapy. However, due to the limited scan field of view (sFOV), the entire cross-section of certain patients may not be fully covered, resulting in projection data truncation. Truncation artifacts in MVCT can compromise registration accuracy with the planned kilovoltage computed tomography (KVCT) and hinder subsequent MVCT-based adaptive planning.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ, UK.
Accurate depth estimation is crucial for many fields, including robotics, navigation, and medical imaging. However, conventional depth sensors often produce low-resolution (LR) depth maps, making detailed scene perception challenging. To address this, enhancing LR depth maps to high-resolution (HR) ones has become essential, guided by HR-structured inputs like RGB or grayscale images.
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