LIVIVO - Search results -

Search results

Result 1 - 10 of total 166

Search options

Article: A review of co-registered transvaginal photoacoustic and ultrasound imaging for ovarian cancer diagnosis.

Zhu, Quing (Ching)

Current opinion in biomedical engineering

2022 Volume 22

Abstract: Ovarian cancer is the deadliest of all gynecological malignancies. When ovarian cancer is detected at an early, localized stage, surgery and chemotherapy can cure 70%-90% of patients, compared with 20% or fewer when it is diagnosed at later stages. ... ...

Abstract	Ovarian cancer is the deadliest of all gynecological malignancies. When ovarian cancer is detected at an early, localized stage, surgery and chemotherapy can cure 70%-90% of patients, compared with 20% or fewer when it is diagnosed at later stages. Clearly, early detection is critical, yet the lack of early symptoms and effective screening tools means that only 20-25% of ovarian cancers are diagnosed early. Photoacoustic imaging (PAI) is an emerging modality that uses a short-pulsed laser to excite tissue. The resulting photoacoustic waves are used to image tissue optical contrast, which is directly related to tissue microvasculature and thus to cancer growth. When co-registered with transvaginal ultrasound (US), PAI offers great promise in diagnosing earlier stage ovarian cancers and distinguishing benign processes from malignant ovarian masses. In this article, we review the limitations of the current imaging tools for early ovarian cancer diagnosis and present recent advances in co-registered PAI/US.
Language	English
Publishing date	2022-04-02
Publishing country	England
Document type	Journal Article
ISSN	2468-4511
ISSN	2468-4511
DOI	10.1016/j.cobme.2022.100381
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Real-time breast lesion classification combining diffuse optical tomography frequency domain data and BI-RADS assessment.

Li, Shuying / Zhang, Menghao / Xue, Minghao / Zhu, Quing

Journal of biophotonics

2024 , Page(s) e202300483

Abstract: Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated potential for breast cancer diagnosis, in which real-time or near real-time diagnosis with high accuracy is desired. However, DOT's relatively slow data processing and image ... ...

Abstract	Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated potential for breast cancer diagnosis, in which real-time or near real-time diagnosis with high accuracy is desired. However, DOT's relatively slow data processing and image reconstruction speeds have hindered real-time diagnosis. Here, we propose a real-time classification scheme that combines US breast imaging reporting and data system (BI-RADS) readings and DOT frequency domain measurements. A convolutional neural network is trained to generate malignancy probability scores from DOT measurements. Subsequently, these scores are integrated with BI-RADS assessments using a support vector machine classifier, which then provides the final diagnostic output. An area under the receiver operating characteristic curve of 0.978 is achieved in distinguishing between benign and malignant breast lesions in patient data without image reconstruction.
Language	English
Publishing date	2024-03-02
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2390063-5
ISSN	1864-0648 ; 1864-063X
ISSN (online)	1864-0648
ISSN	1864-063X
DOI	10.1002/jbio.202300483
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 6723: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article: PA-NeRF, a neural radiance field model for 3D photoacoustic tomography reconstruction from limited Bscan data.

Zou, Yun / Lin, Yixiao / Zhu, Quing

Biomedical optics express

2024 Volume 15, Issue 3, Page(s) 1651–1667

Abstract: We introduce a novel deep-learning-based photoacoustic tomography method called Photoacoustic Tomography Neural Radiance Field (PA-NeRF) for reconstructing 3D volumetric PAT images from limited 2D Bscan data. In conventional 3D volumetric imaging, a 3D ... ...

Abstract	We introduce a novel deep-learning-based photoacoustic tomography method called Photoacoustic Tomography Neural Radiance Field (PA-NeRF) for reconstructing 3D volumetric PAT images from limited 2D Bscan data. In conventional 3D volumetric imaging, a 3D reconstruction requires transducer element data obtained from all directions. Our model employs a NeRF-based PAT 3D reconstruction method, which learns the relationship between transducer element positions and the corresponding 3D imaging. Compared with convolution-based deep-learning models, such as Unet and TransUnet, PA-NeRF does not learn the interpolation process but rather gains insight from 3D photoacoustic imaging principles. Additionally, we introduce a forward loss that improves the reconstruction quality. Both simulation and phantom studies validate the performance of PA-NeRF. Further, we apply the PA-NeRF model to clinical examples to demonstrate its feasibility. To the best of our knowledge, PA-NeRF is the first method in photoacoustic tomography to successfully reconstruct a 3D volume from sparse Bscan data.
Language	English
Publishing date	2024-02-14
Publishing country	United States
Document type	Journal Article
ZDB-ID	2572216-5
ISSN	2156-7085
ISSN	2156-7085
DOI	10.1364/BOE.511807
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Acoustic resolution photoacoustic Doppler flowmetry for assessment of patient rectal cancer blood perfusion.

Kou, Sitai / Leng, Xiandong / Luo, Hongbo / Nie, Haolin / Zhu, Quing

Journal of biomedical optics

2024 Volume 29, Issue Suppl 1, Page(s) S11517

Abstract: Significance: Photoacoustic Doppler flowmetry offers quantitative blood perfusion information in addition to photoacoustic vascular contrast for rectal cancer assessment.: Aim: We aim to develop and validate a correlational Doppler flowmetry ... ...

Abstract	Significance: Photoacoustic Doppler flowmetry offers quantitative blood perfusion information in addition to photoacoustic vascular contrast for rectal cancer assessment. Aim: We aim to develop and validate a correlational Doppler flowmetry utilizing an acoustic resolution photoacoustic microscopy (AR-PAM) system for blood perfusion analysis. Approach: To extract blood perfusion information, we implemented AR-PAM Doppler flowmetry consisting of signal filtering and conditioning, A-line correlation, and angle compensation. We developed flow phantoms and contrast agent to systemically investigate the flowmetry's efficacy in a series of phantom studies. The developed correlational Doppler flowmetry was applied to images collected during Results: The linearity and accuracy of the Doppler flow measurement system were validated in phantom studies. Imaging rectal cancer patients treated with chemoradiation demonstrated the feasibility of using correlational Doppler flowmetry to assess treatment response and distinguish residual cancer from cancer-free tumor bed tissue and normal rectal tissue. Conclusions: A new correlational Doppler flowmetry was developed and validated through systematic phantom evaluations. The results of its application to
MeSH term(s)	Humans ; Laser-Doppler Flowmetry/methods ; Rheology/methods ; Microscopy, Acoustic/methods ; Acoustics ; Rectal Neoplasms/diagnostic imaging ; Photoacoustic Techniques/methods
Language	English
Publishing date	2024-01-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	1309154-2
ISSN	1560-2281 ; 1083-3668
ISSN (online)	1560-2281
ISSN	1083-3668
DOI	10.1117/1.JBO.29.S1.S11517
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 4699: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: A Coregistered Ultrasound and Photoacoustic Imaging Protocol for the Transvaginal Imaging of Ovarian Lesions.

Nie, Haolin / Luo, Hongbo / Chen, Lin / Zhu, Quing

Journal of visualized experiments : JoVE

2023 , Issue 193

Abstract: Ovarian cancer remains the deadliest of all the gynecological malignancies due to the lack of reliable screening tools for early detection and diagnosis. Photoacoustic imaging or tomography (PAT) is an emerging imaging modality that can provide the total ...

Abstract	Ovarian cancer remains the deadliest of all the gynecological malignancies due to the lack of reliable screening tools for early detection and diagnosis. Photoacoustic imaging or tomography (PAT) is an emerging imaging modality that can provide the total hemoglobin concentration (relative scale, rHbT) and blood oxygen saturation (%sO2) of ovarian/adnexal lesions, which are important parameters for cancer diagnosis. Combined with coregistered ultrasound (US), PAT has demonstrated great potential for detecting ovarian cancers and for accurately diagnosing ovarian lesions for effective risk assessment and the reduction of unnecessary surgeries of benign lesions. However, PAT imaging protocols in clinical applications, to our knowledge, largely vary among different studies. Here, we report a transvaginal ovarian cancer imaging protocol that can be beneficial to other clinical studies, especially those using commercial ultrasound arrays for the detection of photoacoustic signals and standard delay-and-sum beamforming algorithms for imaging.
MeSH term(s)	Female ; Humans ; Ovarian Neoplasms/diagnostic imaging ; Ovarian Neoplasms/pathology ; Photoacoustic Techniques/methods ; Ovarian Cysts ; Ultrasonography/methods
Language	English
Publishing date	2023-03-03
Publishing country	United States
Document type	Journal Article ; Video-Audio Media
ZDB-ID	2259946-0
ISSN	1940-087X ; 1940-087X
ISSN (online)	1940-087X
ISSN	1940-087X
DOI	10.3791/64864
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Two-stage classification strategy for breast cancer diagnosis using ultrasound-guided diffuse optical tomography and deep learning.

Zhang, Menghao / Li, Shuying / Xue, Minghao / Zhu, Quing

Journal of biomedical optics

2023 Volume 28, Issue 8, Page(s) 86002

Abstract: Significance: Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated great potential for breast cancer diagnosis in which real-time or near real-time diagnosis with high accuracy is desired.: Aim: We aim to use US-guided DOT to ... ...

Abstract	Significance: Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated great potential for breast cancer diagnosis in which real-time or near real-time diagnosis with high accuracy is desired. Aim: We aim to use US-guided DOT to achieve an automated, fast, and accurate classification of breast lesions. Approach: We propose a two-stage classification strategy with deep learning. In the first stage, US images and histograms created from DOT perturbation measurements are combined to predict benign lesions. Then the non-benign suspicious lesions are passed through to the second stage, which combine US image features, DOT histogram features, and 3D DOT reconstructed images for final diagnosis. Results: The first stage alone identified 73.0% of benign cases without image reconstruction. In distinguishing between benign and malignant breast lesions in patient data, the two-stage classification approach achieved an area under the receiver operating characteristic curve of 0.946, outperforming the diagnoses of all single-modality models and of a single-stage classification model that combines all US images, DOT histogram, and imaging features. Conclusions: The proposed two-stage classification strategy achieves better classification accuracy than single-modality-only models and a single-stage classification model that combines all features. It can potentially distinguish breast cancers from benign lesions in near real-time.
MeSH term(s)	Humans ; Female ; Breast Neoplasms/diagnostic imaging ; Deep Learning ; Breast/diagnostic imaging ; Tomography, Optical ; Ultrasonography, Interventional
Language	English
Publishing date	2023-08-26
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	1309154-2
ISSN	1560-2281 ; 1083-3668
ISSN (online)	1560-2281
ISSN	1083-3668
DOI	10.1117/1.JBO.28.8.086002
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 4699: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article: Ultrasound-enhanced Unet model for quantitative photoacoustic tomography of ovarian lesions.

Zou, Yun / Amidi, Eghbal / Luo, Hongbo / Zhu, Quing

Photoacoustics

2022 Volume 28, Page(s) 100420

Abstract: Quantitative photoacoustic tomography (QPAT) is a valuable tool in characterizing ovarian lesions for accurate diagnosis. However, accurately reconstructing a lesion's optical absorption distributions from photoacoustic signals measured with multiple ... ...

Abstract	Quantitative photoacoustic tomography (QPAT) is a valuable tool in characterizing ovarian lesions for accurate diagnosis. However, accurately reconstructing a lesion's optical absorption distributions from photoacoustic signals measured with multiple wavelengths is challenging because it involves an ill-posed inverse problem with three unknowns: the Grüneisen parameter
Language	English
Publishing date	2022-10-25
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2716706-9
ISSN	2213-5979
ISSN	2213-5979
DOI	10.1016/j.pacs.2022.100420
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Cylindrical lens configuration for optimizing light delivery in a curvilinear endocavity photoacoustic imaging system.

Lin, Yixiao / Kou, Sitai / Zou, Yun / Maslov, Konstantin / Zhu, Quing

Optics letters

2023 Volume 48, Issue 9, Page(s) 2417–2420

Abstract: Curvilinear endocavity ultrasound images capture a wide field of view with a miniature probe. In adapting photoacoustic imaging (PAI) to work with such ultrasound systems, light delivery is challenged by the trade-off between image quality and laser ... ...

Abstract	Curvilinear endocavity ultrasound images capture a wide field of view with a miniature probe. In adapting photoacoustic imaging (PAI) to work with such ultrasound systems, light delivery is challenged by the trade-off between image quality and laser safety concerns. Here, we present two novel, to the best of our knowledge, designs based on cylindrical lenses that are optimized for transvaginal PAI B-scan imaging. Our simulation and experimental results demonstrate that, compared to conventional light delivery methods for PAI imaging, the proposed designs are safer for higher pulse energies and provide deeper imaging and a wider lateral field of view. The proposed designs could also improve the performance of endoscopic co-registered ultrasound/photoacoustic imaging in other clinical applications.
Language	English
Publishing date	2023-04-28
Publishing country	United States
Document type	Journal Article
ISSN	1539-4794
ISSN (online)	1539-4794
DOI	10.1364/OL.486306
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Fusion deep learning approach combining diffuse optical tomography and ultrasound for improving breast cancer classification.

Zhang, Menghao / Xue, Minghao / Li, Shuying / Zou, Yun / Zhu, Quing

Biomedical optics express

2023 Volume 14, Issue 4, Page(s) 1636–1646

Abstract: Diffuse optical tomography (DOT) is a promising technique that provides functional information related to tumor angiogenesis. However, reconstructing the DOT function map of a breast lesion is an ill-posed and underdetermined inverse process. A co- ... ...

Abstract	Diffuse optical tomography (DOT) is a promising technique that provides functional information related to tumor angiogenesis. However, reconstructing the DOT function map of a breast lesion is an ill-posed and underdetermined inverse process. A co-registered ultrasound (US) system that provides structural information about the breast lesion can improve the localization and accuracy of DOT reconstruction. Additionally, the well-known US characteristics of benign and malignant breast lesions can further improve cancer diagnosis based on DOT alone. Inspired by a fusion model deep learning approach, we combined US features extracted by a modified VGG-11 network with images reconstructed from a DOT deep learning auto-encoder-based model to form a new neural network for breast cancer diagnosis. The combined neural network model was trained with simulation data and fine-tuned with clinical data: it achieved an AUC of 0.931 (95% CI: 0.919-0.943), superior to those achieved using US images alone (0.860) or DOT images alone (0.842).
Language	English
Publishing date	2023-03-27
Publishing country	United States
Document type	Journal Article
ZDB-ID	2572216-5
ISSN	2156-7085
ISSN	2156-7085
DOI	10.1364/BOE.486292
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article: Automated pipeline for breast cancer diagnosis using US assisted diffuse optical tomography.

Xue, Minghao / Zhang, Menghao / Li, Shuying / Zou, Yun / Zhu, Quing

Biomedical optics express

2023 Volume 14, Issue 11, Page(s) 6072–6087

Abstract: Ultrasound (US)-guided diffuse optical tomography (DOT) is a portable and non-invasive imaging modality for breast cancer diagnosis and treatment response monitoring. However, DOT data pre-processing and imaging reconstruction often require labor ... ...

Abstract	Ultrasound (US)-guided diffuse optical tomography (DOT) is a portable and non-invasive imaging modality for breast cancer diagnosis and treatment response monitoring. However, DOT data pre-processing and imaging reconstruction often require labor intensive manual processing which hampers real-time diagnosis. In this study, we aim at providing an automated US-assisted DOT pre-processing, imaging and diagnosis pipeline to achieve near real-time diagnosis. We have developed an automated DOT pre-processing method including motion detection, mismatch classification using deep-learning approach, and outlier removal. US-lesion information needed for DOT reconstruction was extracted by a semi-automated lesion segmentation approach combined with a US reading algorithm. A deep learning model was used to evaluate the quality of the reconstructed DOT images and a two-step deep-learning model developed earlier is implemented to provide final diagnosis based on US imaging features and DOT measurements and imaging results. The presented US-assisted DOT pipeline accurately processed the DOT measurements and reconstruction and reduced the procedure time to 2 to 3 minutes while maintained a comparable classification result with manually processed dataset.
Language	English
Publishing date	2023-11-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	2572216-5
ISSN	2156-7085
ISSN	2156-7085
DOI	10.1364/BOE.502244
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

To top

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito