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  1. AU="Bahl, Anisha"
  2. AU="Lee, Michael R"

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  1. Article ; Online: A comparative study of analytical models of diffuse reflectance in homogeneous biological tissues: Gelatin-based phantoms and Monte Carlo experiments.

    Bahl, Anisha / Segaud, Silvere / Xie, Yijing / Shapey, Jonathan / Bergholt, Mads S / Vercauteren, Tom

    Journal of biophotonics

    2024  , Page(s) e202300536

    Abstract: Information about tissue oxygen saturation ( ... ...

    Abstract Information about tissue oxygen saturation (StO
    Language English
    Publishing date 2024-04-14
    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.202300536
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    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)

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  2. Article: Carpal Tunnel Decompression Under Wide Awake Local Anaesthesia No Tourniquet Technique (WALANT): A Cost Effective and Outcome Analysis.

    Faraz, Ahmad / Bahl, Anisha / Khan, Shoaib / Ahmad, Mahmood / Khan, Mohammad N / Mannan, Syed / Jayadeep, Jayachandaran / Kumar, Krishna

    Cureus

    2023  Volume 15, Issue 7, Page(s) e42125

    Abstract: Introduction Wide-awake local anaesthesia with no tourniquet (WALANT) technique is cost-effective, resource-friendly, and safe. This can be used as an alternative to hand surgery procedures in outpatient units. It can be performed in clinics or operating ...

    Abstract Introduction Wide-awake local anaesthesia with no tourniquet (WALANT) technique is cost-effective, resource-friendly, and safe. This can be used as an alternative to hand surgery procedures in outpatient units. It can be performed in clinics or operating rooms. Methods We retrospectively evaluated the outcomes of WALANT for carpal tunnel decompression (CTD) over two years. Measured results include wound infections, relief of symptoms, paraesthesia, haematoma, Visual Analogue Scale (VAS), hospital anxiety and depression scale score (HADS) and cost-effectiveness. Results Eighteen patients underwent CTD under the WALANT technique over two years. VAS score was recorded at 3.1 ± 1.2 during the procedure and 1.67 ± 0.933 at two weeks follow-up. Persistent paraesthesia was found in only one patient at follow-up. Minimal bleeding was recorded during the procedure. No wound infections, revision surgery or post-operative haematoma formation were found. Hospital Anxiety and Depression Scale (HADS) was reported as 4.77 ± 2.1 after surgery. WALANT was also cost-effective, with an overall amount of £20. Conclusion Performing carpal tunnel decompression under WALANT in one stop upper limb clinic is a safe and cost-effective technique with no significant patient-related complications.
    Language English
    Publishing date 2023-07-19
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2747273-5
    ISSN 2168-8184
    ISSN 2168-8184
    DOI 10.7759/cureus.42125
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Book ; Online: A comparative study of analytical models of diffuse reflectance in homogeneous biological tissues

    Bahl, Anisha / Segaud, Silvere / Xie, Yijing / Shapey, Jonathan / Bergholt, Mads / Vercauteren, Tom

    Gelatin based phantoms and Monte Carlo experiments

    2023  

    Abstract: Information about tissue oxygen saturation ($StO_2$) and other related important physiological parameters can be extracted from diffuse reflectance spectra measured through non-contact imaging. Three analytical optical reflectance models for homogeneous, ...

    Abstract Information about tissue oxygen saturation ($StO_2$) and other related important physiological parameters can be extracted from diffuse reflectance spectra measured through non-contact imaging. Three analytical optical reflectance models for homogeneous, semi-infinite, tissue have been proposed (Modified Beer-Lambert, Jacques 1999, Yudovsky 2009) but these have not been directly compared for tissue parameter extraction purposes. We compare these analytical models using Monte Carlo simulated diffuse reflectance spectra and controlled gelatin-based phantoms with measured diffuse reflectance spectra and known ground truth composition parameters. The Yudovsky model performed best against Monte Carlo simulations and measured spectra of tissue phantoms in terms of goodness of fit and parameter extraction accuracy followed closely by Jacques' model. In this study, Yudovsky's model appeared most robust, however our results demonstrated that both Yudovsky and Jacques models are suitable for modelling tissue that can be approximated as a single, homogeneous, semi-infinite slab.

    Comment: Main body: 15 pages, 5 figures, 5 tables. Supplementary: 8 pages, 5 figures, 4 tables
    Keywords Physics - Medical Physics
    Subject code 612
    Publishing date 2023-12-20
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article: Synthetic white balancing for intra-operative hyperspectral imaging.

    Bahl, Anisha / Horgan, Conor C / Janatka, Mirek / MacCormac, Oscar J / Noonan, Philip / Xie, Yijing / Qiu, Jianrong / Cavalcanti, Nicola / Fürnstahl, Philipp / Ebner, Michael / Bergholt, Mads S / Shapey, Jonathan / Vercauteren, Tom

    Journal of medical imaging (Bellingham, Wash.)

    2023  Volume 10, Issue 4, Page(s) 46001

    Abstract: Purpose: Hyperspectral imaging shows promise for surgical applications to non-invasively provide spatially resolved, spectral information. For calibration purposes, a white reference image of a highly reflective Lambertian surface should be obtained ... ...

    Abstract Purpose: Hyperspectral imaging shows promise for surgical applications to non-invasively provide spatially resolved, spectral information. For calibration purposes, a white reference image of a highly reflective Lambertian surface should be obtained under the same imaging conditions. Standard white references are not sterilizable and so are unsuitable for surgical environments. We demonstrate the necessity for
    Approach: The use of references obtained at different distances and lighting conditions to the subject were examined. Spectral and color reconstructions were compared with standard measurements qualitatively and quantitatively, using
    Results: Improper white balancing leads to increases in all quantitative and qualitative errors. Synthetic references achieve median pixel-by-pixel errors lower than 6.5% and produce similar reconstructions and errors to an ideal reference. The algorithm integrated well into surgical workflow, achieving median pixel-by-pixel errors of 4.77% while maintaining good spectral and color reconstruction.
    Conclusions: We demonstrate the importance of
    Language English
    Publishing date 2023-07-24
    Publishing country United States
    Document type Journal Article
    ISSN 2329-4302
    ISSN 2329-4302
    DOI 10.1117/1.JMI.10.4.046001
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Deep learning approach for hyperspectral image demosaicking, spectral correction and high-resolution RGB reconstruction.

    Li, Peichao / Ebner, Michael / Noonan, Philip / Horgan, Conor / Bahl, Anisha / Ourselin, Sébastien / Shapey, Jonathan / Vercauteren, Tom

    Computer methods in biomechanics and biomedical engineering. Imaging & visualization

    2021  Volume 10, Issue 4, Page(s) 409–417

    Abstract: Hyperspectral imaging is one of the most promising techniques for intraoperative tissue characterisation. Snapshot mosaic cameras, which can capture hyperspectral data in a single exposure, have the potential to make a real-time hyperspectral imaging ... ...

    Abstract Hyperspectral imaging is one of the most promising techniques for intraoperative tissue characterisation. Snapshot mosaic cameras, which can capture hyperspectral data in a single exposure, have the potential to make a real-time hyperspectral imaging system for surgical decision-making possible. However, optimal exploitation of the captured data requires solving an ill-posed demosaicking problem and applying additional spectral corrections. In this work, we propose a supervised learning-based image demosaicking algorithm for snapshot hyperspectral images. Due to the lack of publicly available medical images acquired with snapshot mosaic cameras, a synthetic image generation approach is proposed to simulate snapshot images from existing medical image datasets captured by high-resolution, but slow, hyperspectral imaging devices. Image reconstruction is achieved using convolutional neural networks for hyperspectral image super-resolution, followed by spectral correction using a sensor-specific calibration matrix. The results are evaluated both quantitatively and qualitatively, showing clear improvements in image quality compared to a baseline demosaicking method using linear interpolation. Moreover, the fast processing time of 45 ms of our algorithm to obtain super-resolved RGB or oxygenation saturation maps per image for a state-of-the-art snapshot mosaic camera demonstrates the potential for its seamless integration into real-time surgical hyperspectral imaging applications.
    Language English
    Publishing date 2021-11-30
    Publishing country England
    Document type Journal Article
    ISSN 2168-1163
    ISSN 2168-1163
    DOI 10.1080/21681163.2021.1997646
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Lightfield hyperspectral imaging in neuro-oncology surgery: an IDEAL 0 and 1 study.

    MacCormac, Oscar / Noonan, Philip / Janatka, Mirek / Horgan, Conor C / Bahl, Anisha / Qiu, Jianrong / Elliot, Matthew / Trotouin, Théo / Jacobs, Jaco / Patel, Sabina / Bergholt, Mads S / Ashkan, Keyoumars / Ourselin, Sebastien / Ebner, Michael / Vercauteren, Tom / Shapey, Jonathan

    Frontiers in neuroscience

    2023  Volume 17, Page(s) 1239764

    Abstract: Introduction: Hyperspectral imaging (HSI) has shown promise in the field of intra-operative imaging and tissue differentiation as it carries the capability to provide real-time information invisible to the naked eye whilst remaining label free. Previous ...

    Abstract Introduction: Hyperspectral imaging (HSI) has shown promise in the field of intra-operative imaging and tissue differentiation as it carries the capability to provide real-time information invisible to the naked eye whilst remaining label free. Previous iterations of intra-operative HSI systems have shown limitations, either due to carrying a large footprint limiting ease of use within the confines of a neurosurgical theater environment, having a slow image acquisition time, or by compromising spatial/spectral resolution in favor of improvements to the surgical workflow. Lightfield hyperspectral imaging is a novel technique that has the potential to facilitate video rate image acquisition whilst maintaining a high spectral resolution. Our pre-clinical and first-in-human studies (IDEAL 0 and 1, respectively) demonstrate the necessary steps leading to the first
    Methods: A lightfield hyperspectral camera (Cubert Ultris ×50) was integrated in a bespoke imaging system setup so that it could be safely adopted into the open neurosurgical workflow whilst maintaining sterility. Our system allowed the surgeon to capture
    Results: Focusing on our IDEAL 1 study results, hyperspectral information was acquired from the cerebellum and associated meningioma with minimal disruption to the neurosurgical workflow. To the best of our knowledge, this is the first demonstration of HSI acquisition with 100+ spectral bands at a frame rate over 1Hz in surgery.
    Discussion: This work demonstrated that a lightfield hyperspectral imaging system not only meets the design criteria and specifications outlined in an IDEAL-0 (pre-clinical) study, but also that it can translate into clinical practice as illustrated by a successful first in human study (IDEAL 1). This opens doors for further development and optimisation, given the increasing evidence that hyperspectral imaging can provide live, wide-field, and label-free intra-operative imaging and tissue differentiation.
    Language English
    Publishing date 2023-09-18
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2411902-7
    ISSN 1662-453X ; 1662-4548
    ISSN (online) 1662-453X
    ISSN 1662-4548
    DOI 10.3389/fnins.2023.1239764
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Accurate real-time F

    Petralia, Lorenzo S / Bahl, Anisha / Peverall, Rob / Richmond, Graham / Couper, John H / Hancock, Gus / Robbins, Peter A / Ritchie, Grant A D

    Journal of breath research

    2020  Volume 14, Issue 4, Page(s) 47102

    Abstract: The fraction of exhaled nitric oxide ( ... ...

    Abstract The fraction of exhaled nitric oxide (F
    MeSH term(s) Adult ; Breath Tests/methods ; Female ; Humans ; Male ; Middle Aged ; Optical Phenomena ; Spectrum Analysis/methods
    Language English
    Publishing date 2020-08-14
    Publishing country England
    Document type Journal Article
    ZDB-ID 2381007-5
    ISSN 1752-7163 ; 1752-7155
    ISSN (online) 1752-7163
    ISSN 1752-7155
    DOI 10.1088/1752-7163/ab9c31
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Book ; Online: Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction

    Li, Peichao / Ebner, Michael / Noonan, Philip / Horgan, Conor / Bahl, Anisha / Ourselin, Sebastien / Shapey, Jonathan / Vercauteren, Tom

    2021  

    Abstract: Hyperspectral imaging is one of the most promising techniques for intraoperative tissue characterisation. Snapshot mosaic cameras, which can capture hyperspectral data in a single exposure, have the potential to make a real-time hyperspectral imaging ... ...

    Abstract Hyperspectral imaging is one of the most promising techniques for intraoperative tissue characterisation. Snapshot mosaic cameras, which can capture hyperspectral data in a single exposure, have the potential to make a real-time hyperspectral imaging system for surgical decision-making possible. However, optimal exploitation of the captured data requires solving an ill-posed demosaicking problem and applying additional spectral corrections to recover spatial and spectral information of the image. In this work, we propose a deep learning-based image demosaicking algorithm for snapshot hyperspectral images using supervised learning methods. Due to the lack of publicly available medical images acquired with snapshot mosaic cameras, a synthetic image generation approach is proposed to simulate snapshot images from existing medical image datasets captured by high-resolution, but slow, hyperspectral imaging devices. Image reconstruction is achieved using convolutional neural networks for hyperspectral image super-resolution, followed by cross-talk and leakage correction using a sensor-specific calibration matrix. The resulting demosaicked images are evaluated both quantitatively and qualitatively, showing clear improvements in image quality compared to a baseline demosaicking method using linear interpolation. Moreover, the fast processing time of~45\,ms of our algorithm to obtain super-resolved RGB or oxygenation saturation maps per image frame for a state-of-the-art snapshot mosaic camera demonstrates the potential for its seamless integration into real-time surgical hyperspectral imaging applications.
    Keywords Electrical Engineering and Systems Science - Image and Video Processing ; Computer Science - Computer Vision and Pattern Recognition
    Subject code 006
    Publishing date 2021-09-03
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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