Besides the application of EIT in the intensive care unit it has recently also been used in spontaneously breathing patients suffering from asthma bronchiole, cystic fibrosis (CF) or chronic obstructive pulmonary disease (COPD). In these cases large thorax excursions during deep inspiration, e.g. during lung function testing, lead to artifacts in the reconstructed images. In this paper we introduce a new approach to compensate for image artifacts resulting from excursion induced changes in boundary voltages. It is shown in a simulation study that boundary voltage change due to thorax excursion on a homogeneous model can be used to modify the measured voltages and thus reduce the impact of thorax excursion on the reconstructed images. The applicability of the method on human subjects is demonstrated utilizing a motion-tracking-system. The proposed technique leads to fewer artifacts in the reconstructed images and improves image quality without substantial increase in computational effort, making the approach suitable for real-time imaging of lung ventilation. This might help to establish EIT as a supplemental tool for lung function tests in spontaneously breathing patients to support clinicians in diagnosis and monitoring of disease progression.
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http://dx.doi.org/10.1088/0967-3334/37/9/1605 | DOI Listing |
Sensors (Basel)
January 2025
Department of Biomedical and Robotics Engineering, Incheon National University, Incheon 22012, Republic of Korea.
With the rise of modern healthcare monitoring, heart rate (HR) estimation using remote photoplethysmography (rPPG) has gained attention for its non-contact, continuous tracking capabilities. However, most HR estimation methods rely on stable, fixed sampling intervals, while practical image capture often involves irregular frame rates and missing data, leading to inaccuracies in HR measurements. This study addresses these issues by introducing low-complexity timing correction methods, including linear, cubic, and filter interpolation, to improve HR estimation from rPPG signals under conditions of irregular sampling and data loss.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Shanghai Film Academy, Shanghai University, Shanghai 200072, China.
The advancement of neural radiance fields (NeRFs) has facilitated the high-quality 3D reconstruction of complex scenes. However, for most NeRFs, reconstructing 3D tissues from endoscopy images poses significant challenges due to the occlusion of soft tissue regions by invalid pixels, deformations in soft tissue, and poor image quality, which severely limits their application in endoscopic scenarios. To address the above issues, we propose a novel framework to reconstruct high-fidelity soft tissue scenes from low-quality endoscopic images.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Electronic and Communication Engineering, Sun Yat-sen University, Shenzhen 518000, China.
Exploring the relationships between plant phenotypes and genetic information requires advanced phenotypic analysis techniques for precise characterization. However, the diversity and variability of plant morphology challenge existing methods, which often fail to generalize across species and require extensive annotated data, especially for 3D datasets. This paper proposes a zero-shot 3D leaf instance segmentation method using RGB sensors.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Faculty of Land and Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China.
To address the challenges of missed detections caused by insufficient shape and texture features and blurred boundaries in existing detection methods, this paper introduces a novel moving vehicle detection approach for satellite videos. The proposed method leverages frame difference and convolution to effectively integrate spatiotemporal information. First, a frame difference module (FDM) is designed, combining frame difference and convolution.
View Article and Find Full Text PDFJ Clin Med
January 2025
Department of Plastic and Reconstructive Surgery, Chonnam National University Hospital, Chonnam National University Medical School, 42 Jebong-ro, Dong-gu, Gwangju 61469, Republic of Korea.
: Spontaneous chest wall hematomas are rare but potentially life-threatening complications, particularly in patients with multiple comorbidities such as those undergoing hemodialysis. This case report aims to highlight the significance of early diagnosis and appropriate management in preventing complications associated with this condition. : We report the case of a 79-year-old man with end-stage renal disease on hemodialysis, presenting with a large spontaneous hematoma (18.
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