Vascular recognition system based on photoacoustic detection

Zhang, Chuncheng; Liu, Guodong; Xie, Zhihua; Shu, Zhenghua; Ren, Zhong; Yao, Qingkai

doi:10.2351/7.0000261

Cited by 5 publications

(3 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These systems are crafted by integrating diverse methodologies for optical illumination and acoustic signal detection [ 62 ]. Significantly, PAI has attained a fine spatial resolution at the micron level alongside delivering satisfactory image quality for vascular structures [ 63 ]. PAI also has functional capability to provide detailed information, such as blood oxygen, blood flow and temperature of local lesion, to assist in the diagnosis of different kinds of vascular anomalies [ 64 ].…”

Section: Nanotechnology Applying In Diagnosis Of Vascular Anomaliesmentioning

confidence: 99%

Recent advances in nanomaterial-driven strategies for diagnosis and therapy of vascular anomalies

Geng,

Zou,

et al. 2024

J Nanobiotechnol

View full text Add to dashboard Cite

Nanotechnology has demonstrated immense potential in various fields, especially in biomedical field. Among these domains, the development of nanotechnology for diagnosing and treating vascular anomalies has garnered significant attention. Vascular anomalies refer to structural and functional anomalies within the vascular system, which can result in conditions such as vascular malformations and tumors. These anomalies can significantly impact the quality of life of patients and pose significant health concerns. Nanoscale contrast agents have been developed for targeted imaging of blood vessels, enabling more precise identification and characterization of vascular anomalies. These contrast agents can be designed to bind specifically to abnormal blood vessels, providing healthcare professionals with a clearer view of the affected areas. More importantly, nanotechnology also offers promising solutions for targeted therapeutic interventions. Nanoparticles can be engineered to deliver drugs directly to the site of vascular anomalies, maximizing therapeutic effects while minimizing side effects on healthy tissues. Meanwhile, by incorporating functional components into nanoparticles, such as photosensitizers, nanotechnology enables innovative treatment modalities such as photothermal therapy and photodynamic therapy. This review focuses on the applications and potential of nanotechnology in the imaging and therapy of vascular anomalies, as well as discusses the present challenges and future directions. Graphical Abstract

show abstract

Section: Nanotechnology Applying In Diagnosis Of Vascular Anomaliesmentioning

confidence: 99%

Recent advances in nanomaterial-driven strategies for diagnosis and therapy of vascular anomalies

Geng,

Zou,

et al. 2024

J Nanobiotechnol

View full text Add to dashboard Cite

show abstract

“…In this technique, light signals that are preferentially absorbed by the tissue cause the generation of acoustic waves, which are subsequently detected and imaged by a conventional ultrasound (US) transducer. Photoacoustic imaging is widely used for the detection and treatment of cancer, vascular monitoring, medication delivery, surgical navigation, and metal implant detection [6][7][8][9][10]. However, radioactivity artifacts are often present in photoacoustic images, which can pose diagnostic and therapeutic challenges for clinicians [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Realizes Photoacoustic Imaging Artifact Removal

He,

Chen,

Jiang

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

Photoacoustic imaging integrates the strengths of optics and ultrasound, offering high resolution, depth penetration, and multimodal imaging capabilities. Practical considerations with instrumentation and geometry limit the number of available acoustic sensors and their “view” of the imaging target, which result in image reconstruction artifacts degrading image quality. To address this problem, YOLOv8-Pix2Pix is proposed as a hybrid artifact-removal algorithm, which is advantageous in comprehensively eliminating various types of artifacts and effectively restoring image details compared to existing algorithms. The proposed algorithm demonstrates superior performance in artifact removal and segmentation of photoacoustic images of brain tumors. For the purpose of further expanding its application fields and aligning with actual clinical needs, an experimental system for photoacoustic detection is designed in this paper to be verified. The experimental results show that the processed images are better than the pre-processed images in terms of reconstruction metrics PSNR and SSIM, and also the segmentation performance is significantly improved, which provides an effective solution for the further development of photoacoustic imaging technology.

show abstract

“…The majority of attention was devoted to fingerprints [10][11][12], but other characteristics like palmprints [13] and hand geometry [14][15][16] have also been investigated. Additionally, 3D vein patterns were extracted using power Doppler techniques [17][18][19] and photoacoustics [20][21][22][23]. However, even if quite accurate patterns were achieved, the acquisition time proved to be too long for both technologies.…”

Section: Introductionmentioning

confidence: 99%

3D Vascular Pattern Extraction from Grayscale Volumetric Ultrasound Images for Biometric Recognition Purposes

Iula

Vizzuso

2022

Applied Sciences

View full text Add to dashboard Cite

Recognition systems based on palm veins are gaining increasing attention as they are highly distinctive and very hard to counterfeit. Most popular systems are based on infrared radiation; they have the merit to be contactless but can provide only 2D patterns. Conversely, 3D patterns can be achieved with Doppler or photoacoustic methods, but these approaches require too long of an acquisition time. In this work, a method for extracting 3D vascular patterns from conventional grayscale volumetric images of the human hand, which can be collected in a short time, is proposed for the first time. It is based on the detection of low-brightness areas in B-mode images. Centroids of these areas in successive B-mode images are then linked through a minimum distance criterion. Preliminary verification and identification results, carried out on a database previously established for extracting 3D palmprint features, demonstrated good recognition performances: EER = 2%, ROC AUC = 99.92%, and an identification rate of 100%. As further merit, 3D vein pattern features can be fused to 3D palmprint features to implement a costless multimodal recognition system.

show abstract

Vascular recognition system based on photoacoustic detection

Cited by 5 publications

References 32 publications

Recent advances in nanomaterial-driven strategies for diagnosis and therapy of vascular anomalies

Recent advances in nanomaterial-driven strategies for diagnosis and therapy of vascular anomalies

Deep Learning Realizes Photoacoustic Imaging Artifact Removal

3D Vascular Pattern Extraction from Grayscale Volumetric Ultrasound Images for Biometric Recognition Purposes

Contact Info

Product

Resources

About