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Bioengineering
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Advancements in Medical Imaging Technology
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Advancements in Medical Imaging Technology

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".

Deadline for manuscript submissions: closed (31 May 2025) | Viewed by 4963

Special Issue Editor

Prof. Dr. Yuling Yan

E-Mail Website
Guest Editor
School of Engineering, Santa Clara University, Santa Clara, CA 95053, USA
Interests: biosignal processing; bioimaging; AI-assisted disease classification; laryngeal dynamics and physiology; biomedical visualization; brain-computer Interface
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Special Issue provides a platform for researchers to present their latest breakthroughs and discoveries in diagnostic medical imaging. Ongoing progress in hardware innovation and image reconstruction techniques, alongside post-processing methods integrating computer-aided diagnosis and cutting-edge deep learning technologies, offer significant potential to transform various aspects of healthcare. These advancements hold promise in improving disease prognosis, refining diagnostic accuracy and enabling personalized treatment strategies, ultimately revolutionizing patient care.

This issue will comprehensively cover a diverse array of topics related to diagnostic imaging modalities, encompassing CT, high-field and low-field MRI, ultrasonography and other imaging techniques commonly employed in disease diagnosis and prognosis. We encourage contributions from a wide spectrum of professionals, including engineers, medical practitioners and interdisciplinary teams possessing combined expertise in medicine and biomedical engineering. By fostering collaborations and knowledge exchange, our ultimate goal is to advance the field of medical imaging, driving innovation and improving patient outcomes on a global scale.

Prof. Dr. Yuling Yan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • diagnostic imaging
  • image reconstruction and analysis
  • computer-aided diagnosis
  • deep learning

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Published Papers (6 papers)

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Research

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21 pages, 4915 KiB  
Article
Eliminating the Need for Anesthesia in Sleep Endoscopy: A Comparative Study of Traditional Nasopharyngoscope Design Versus NasoLens
by Yen-Tsung Lin, Chih-Wei Shih, Nathan Chen, Hsin-Tzu Lu, Woei-Chyn Chu and Kuang-Chao Chen
Bioengineering 2025, 12(6), 572; https://doi.org/10.3390/bioengineering12060572 - 26 May 2025
Viewed by 241
Abstract
This study investigates the potential of a novel sleep endoscope, NasoLens, to eliminate the need for anesthesia in sleep endoscopy. We assess NasoLens’ safety, maneuverability, and ability to allow sleep without sedatives, aiming to improve the overall patient experience and reduce risks associated [...] Read more.
This study investigates the potential of a novel sleep endoscope, NasoLens, to eliminate the need for anesthesia in sleep endoscopy. We assess NasoLens’ safety, maneuverability, and ability to allow sleep without sedatives, aiming to improve the overall patient experience and reduce risks associated with anesthesia. Sleep endoscopy is commonly performed under anesthesia, which introduces risks, increases costs, and can limit accessibility. NasoLens’ design aims to address these challenges by improving patient comfort and enhancing maneuverability, eliminating the need for anesthesia. This could provide a safer, more cost-effective alternative for patients, particularly those at higher risk for anesthesia-related complications. NasoLens distinguishes itself with its smaller size, teardrop-shaped head, specialized camera angle for better visualization, and an integrated microphone for real-time auditory monitoring. These features enable NasoLens to offer improved maneuverability and comfort, compared to traditional nasopharyngoscopes, while enhancing diagnostic accuracy. These design innovations could revolutionize clinical practice by minimizing anesthesia-related risks, reducing procedural costs, and improving both procedural efficiency and patient satisfaction. With its ability to allow natural sleep without sedation, NasoLens has the potential to improve patient satisfaction, procedural outcomes, and expand the feasibility of sleep endoscopy into more accessible clinical settings, making it a promising alternative to traditional models. Full article
(This article belongs to the Special Issue Advancements in Medical Imaging Technology)
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17 pages, 12183 KiB  
Article
Triplanar Point Cloud Reconstruction of Head Skin Surface from Computed Tomography Images in Markerless Image-Guided Surgery
by Jurica Cvetić, Bojan Šekoranja, Marko Švaco and Filip Šuligoj
Bioengineering 2025, 12(5), 498; https://doi.org/10.3390/bioengineering12050498 - 8 May 2025
Viewed by 397
Abstract
Accurate preoperative image processing in markerless image-guided surgeries is an important task. However, preoperative planning highly depends on the quality of medical imaging data. In this study, a novel algorithm for outer skin layer extraction from head computed tomography (CT) scans is presented [...] Read more.
Accurate preoperative image processing in markerless image-guided surgeries is an important task. However, preoperative planning highly depends on the quality of medical imaging data. In this study, a novel algorithm for outer skin layer extraction from head computed tomography (CT) scans is presented and evaluated. Axial, sagittal, and coronal slices are processed separately to generate spatial data. Each slice is binarized using manually defined Hounsfield unit (HU) range thresholding to create binary images from which valid contours are extracted. The individual points of each contour are then projected into three-dimensional (3D) space using slice spacing and origin information, resulting in uniplanar point clouds. These point clouds are then fused through geometric addition into a single enriched triplanar point cloud. A two-step downsampling process is applied, first at the uniplanar level and then after merging, using a voxel size of 1 mm. Across two independent datasets with a total of 83 individuals, the merged cloud approach yielded an average of 11.61% more unique points compared to the axial cloud. The validity of the triplanar point cloud reconstruction was confirmed by a root mean square (RMS) registration error of 0.848 ± 0.035 mm relative to the ground truth models. These results establish the proposed algorithm as robust and accurate across different CT scanners and acquisition parameters, supporting its potential integration into patient registration for markerless image-guided surgeries. Full article
(This article belongs to the Special Issue Advancements in Medical Imaging Technology)
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12 pages, 693 KiB  
Article
Haralick Texture Analysis for Differentiating Suspicious Prostate Lesions from Normal Tissue in Low-Field MRI
by Dang Bich Thuy Le, Ram Narayanan, Meredith Sadinski, Aleksandar Nacev, Yuling Yan and Srirama S. Venkataraman
Bioengineering 2025, 12(1), 47; https://doi.org/10.3390/bioengineering12010047 - 9 Jan 2025
Viewed by 805
Abstract
This study evaluates the feasibility of using Haralick texture analysis on low-field, T2-weighted MRI images for detecting prostate cancer, extending current research from high-field MRI to the more accessible and cost-effective low-field MRI. A total of twenty-one patients with biopsy-proven prostate cancer (Gleason [...] Read more.
This study evaluates the feasibility of using Haralick texture analysis on low-field, T2-weighted MRI images for detecting prostate cancer, extending current research from high-field MRI to the more accessible and cost-effective low-field MRI. A total of twenty-one patients with biopsy-proven prostate cancer (Gleason score 4+3 or higher) were included. Before transperineal biopsy guided by low-field (58–74mT) MRI, a radiologist annotated suspicious regions of interest (ROIs) on high-field (3T) MRI. Rigid image registration was performed to align corresponding regions on both high- and low-field images, ensuring an accurate propagation of annotations to the co-registered low-field images for texture feature calculations. For each cancerous ROI, a matching ROI of identical size was drawn in a non-suspicious region presumed to be normal tissue. Four Haralick texture features (Energy, Correlation, Contrast, and Homogeneity) were extracted and compared between cancerous and non-suspicious ROIs. Two extraction methods were used: the direct computation of texture measures within the ROIs and a sliding window technique generating texture maps across the prostate from which average values were derived. The results demonstrated statistically significant differences in texture features between cancerous and non-suspicious regions. Specifically, Energy and Homogeneity were elevated (p-values: <0.00001–0.004), while Contrast and Correlation were reduced (p-values: <0.00001–0.03) in cancerous ROIs. These findings suggest that Haralick texture features are both feasible and informative for differentiating abnormalities, offering promise in assisting prostate cancer detection on low-field MRI. Full article
(This article belongs to the Special Issue Advancements in Medical Imaging Technology)
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13 pages, 5448 KiB  
Article
Skull Impact on Photoacoustic Imaging of Multi-Layered Brain Tissues with Embedded Blood Vessel Under Different Optical Source Types: Modeling and Simulation
by Xi Yang, Chengpeng Chai, Yun-Hsuan Chen and Mohamad Sawan
Bioengineering 2025, 12(1), 40; https://doi.org/10.3390/bioengineering12010040 - 7 Jan 2025
Cited by 1 | Viewed by 954
Abstract
Skulls with high optical scattering and acoustic attenuation are a great challenge for photoacoustic imaging for human beings. To explore and improve photoacoustic generation and propagation, we conducted the photoacoustic simulation and image reconstruction of the multi-layer brain model with an embedded blood [...] Read more.
Skulls with high optical scattering and acoustic attenuation are a great challenge for photoacoustic imaging for human beings. To explore and improve photoacoustic generation and propagation, we conducted the photoacoustic simulation and image reconstruction of the multi-layer brain model with an embedded blood vessel under different optical source types. Based on the optical simulation results under different types of optical sources, we explored the characteristics of reconstructed images obtained from acoustic simulations with and without skull conditions. Specifically, we focused on the detection of blood vessels and evaluated the image reconstruction features, morphological characteristics, and intensity of variations in the target vessels using optical and acoustic simulations. The results showed that under the initial PA signals, the types of optical source types corresponding to the strongest and weakest photoacoustic signals at different positions within the target region were consistent, while the optical source types were different in the reconstructed images. This study revealed the characteristics of acoustic signal transmission with and without skull conditions and its impact on image reconstruction. It further provides a theoretical basis for the selection of optical sources. Full article
(This article belongs to the Special Issue Advancements in Medical Imaging Technology)
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11 pages, 2682 KiB  
Article
Visualization of Cerebrospinal Fluid Outflow and Egress along the Nerve Roots of the Lumbar Spine
by Diana Vucevic, Vadim Malis, Won C. Bae, Hideki Ota, Koichi Oshio, Marin A. McDonald and Mitsue Miyazaki
Bioengineering 2024, 11(7), 708; https://doi.org/10.3390/bioengineering11070708 - 12 Jul 2024
Cited by 1 | Viewed by 1446
Abstract
Intrinsic cerebrospinal fluid (CSF) dynamics in the brain have been extensively studied, particularly the egress sites of tagged intrinsic CSF in the meninges. Although spinal CSF recirculates within the central nervous system (CNS), we hypothesized that CSF outflows from the lumbar spinal canal. [...] Read more.
Intrinsic cerebrospinal fluid (CSF) dynamics in the brain have been extensively studied, particularly the egress sites of tagged intrinsic CSF in the meninges. Although spinal CSF recirculates within the central nervous system (CNS), we hypothesized that CSF outflows from the lumbar spinal canal. We aimed to visualize and semi-quantify the outflow using non-contrast MRI techniques. We utilized a 3 Tesla clinical MRI with a 16-channel spine coil, employing time–spatial labeling inversion (Time-SLIP) with tag-on and tag-off acquisitions, T2-weighted coronal 2D fluid-attenuated inversion recovery (FLAIR) and T2-weighted coronal 3D centric ky-kz single-shot FSE (cSSFSE). Images were acquired using time–spatial labeling inversion pulse (Time-SLIP) with tag-on and tag-off acquisitions with varying TI periods. Ten healthy volunteers with no known spinal diseases participated. Variations in tagged CSF outflow were observed across different thoracolumbar nerve root segments in all participants. We quantified CSF outflow at all lumbar levels and the psoas region. There was no significant difference among the ROIs for signal intensity. The tagged CSF outflow from the spinal canal is small but demonstrates egress to surrounding tissues. This finding may pave the way for exploring intrathecal drug delivery, understanding of CSF-related pathologies and its potential as a biomarker for peripheral neuropathy and radiculopathy. Full article
(This article belongs to the Special Issue Advancements in Medical Imaging Technology)
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Other

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23 pages, 2425 KiB  
Systematic Review
Emerging Image-Guided Navigation Techniques for Cardiovascular Interventions: A Scoping Review
by Majid Roshanfar, Mohammadhossein Salimi, Sun-Joo Jang, Albert J. Sinusas, Jiwon Kim and Bobak Mosadegh
Bioengineering 2025, 12(5), 488; https://doi.org/10.3390/bioengineering12050488 - 2 May 2025
Viewed by 431
Abstract
Background: Image-guided navigation has revolutionized precision cardiac interventions, yet current technologies face critical limitations in real-time guidance and procedural accuracy. Method: Here, we comprehensively evaluate state-of-the-art imaging modalities, from conventional fluoroscopy to emerging hybrid systems, analyzing their applications across coronary, structural, and electrophysiological [...] Read more.
Background: Image-guided navigation has revolutionized precision cardiac interventions, yet current technologies face critical limitations in real-time guidance and procedural accuracy. Method: Here, we comprehensively evaluate state-of-the-art imaging modalities, from conventional fluoroscopy to emerging hybrid systems, analyzing their applications across coronary, structural, and electrophysiological interventions. Results: We demonstrate that novel approaches combining optical coherence tomography with near-infrared spectroscopy or fluorescence achieve unprecedented plaque characterization and procedural guidance through simultaneous structural and molecular imaging. Our analysis reveals key challenges, including imaging artifacts and resolution constraints, while highlighting recent technological solutions incorporating artificial intelligence and robotics. We show that non-imaging alternatives, such as fiber optic real-shape sensing and electromagnetic tracking, complement traditional techniques by providing real-time navigation without radiation exposure. This paper also discusses the integration of image-guided navigation techniques into augmented reality systems and patient-specific modeling, highlighting initial clinical studies that demonstrate their significant promise in reducing procedural times and improving accuracy. These findings establish a framework for next-generation cardiac interventions, emphasizing the critical role of multimodal imaging platforms enhanced by AI-driven decision support. Conclusions: We conclude that continued innovation in hybrid imaging systems, coupled with advances in automation, will be essential for optimizing procedural outcomes and expanding access to complex cardiac interventions. Full article
(This article belongs to the Special Issue Advancements in Medical Imaging Technology)
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