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Purpose: This paper investigates the capabilities of a dual-rotation C-arm cone-beam computed tomography (CBCT) framework to improve non-contrast-enhanced low-contrast detection for full volume or volume-of-interest (VOI) brain imaging.
Method: The idea is to associate two C-arm short-scan rotational acquisitions (spins): one over the full detector field of view (FOV) at low dose, and one collimated to deliver a higher dose to the central densest parts of the head. The angular sampling performed by each spin is allowed to vary in terms of number of views and angular positions. Collimated data is truncated and does not contain measurement of the incoming X-ray intensities in air (air calibration). When targeting full volume reconstruction, the method is intended to act as a virtual bow-tie. When targeting VOI imaging, the method is intended to provide the minimum full detector FOV data that sufficiently corrects for truncation artifacts. A single dedicated iterative algorithm is described that handles all proposed sampling configurations despite truncation and absence of air calibration.
Results: Full volume reconstruction of dual-rotation simulations and phantom acquisitions are shown to have increased low-contrast detection for less dose, with respect to a single-rotation acquisition. High CNR values were obtained on 1% inserts of the Catphan® 515 module in 0.94 mm thick slices. Image quality for VOI imaging was preserved from truncation artifacts even with less than 10 non-truncated views, without using the sparsity a priori common to such context.
Conclusion: A flexible dual-rotation acquisition and reconstruction framework is proposed that has the potential to improve low-contrast detection in clinical C-arm brain soft-tissue imaging.
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http://dx.doi.org/10.1002/mp.12247 | DOI Listing |
Digit Health
September 2025
Department of Respiratory and Critical Care Medicine, The Sixth Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Objective: Accurate segmentation of breast lesions, especially small ones, remains challenging in digital mammography due to complex anatomical structures and low-contrast boundaries. This study proposes DVF-YOLO-Seg, a two-stage segmentation framework designed to improve feature extraction and enhance small-lesion detection performance in mammographic images.
Methods: The proposed method integrates an enhanced YOLOv10-based detection module with a segmentation stage based on the Visual Reference Prompt Segment Anything Model (VRP-SAM).
J Med Eng Technol
September 2025
Department of Computer Engineering and Information Technology, Faculty of Electrical and Computer Engineering, Graduate University of Advanced Technology, Kerman, Iran.
Diabetic retinopathy is a chronic and progressive eye disease in which the human retina is affected by an increase in the amount of insulin in the blood. Diabetic retinopathy, if not detected and treated in time, threatens the patient's vision and eventually causes complete blindness. Among various clinical symptoms, microaneurysm appears as the first sign of diabetic retinopathy.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
September 2025
Accurate detection and localization of microbial targets are critical for microbial trajectory tracking and analysis. However, microscopic microorganism images often exhibit low contrast and mutual occlusion between targets, which pose significant challenges for microbial object accuracy detection due to insufficient distinguishable shallow-layer information and occluded targets inadequate representation. To address these issues, a novel method of SMA-YOLOv8s is proposed for microbial object detection.
View Article and Find Full Text PDFSensors (Basel)
August 2025
CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.
Accurate segmentation of fine roots in field rhizotron imagery is essential for high-throughput root system analysis but remains challenging due to limitations of traditional methods. Traditional methods for root quantification (e.g.
View Article and Find Full Text PDFJ Clin Med
August 2025
Department of Optics and Optometry, Faculty of Optics and Optometry, Universidad Complutense de Madrid, 28037 Madrid, Spain.
Standard visual acuity (VA) is often preserved in early retinitis pigmentosa (RP), limiting its value as a marker of functional impairment. Alternative measures such as low-luminance deficit (LLD) and low-contrast deficit (LCD) may detect earlier changes in cone function. This study aimed to evaluate the diagnostic utility of these measures in RP patients under photopic and mesopic conditions.
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