Literature DB >> 34015146

Deep Learning in Biomedical Optics.

Lei Tian1, Brady Hunt2, Muyinatu A Lediju Bell3,4,5, Ji Yi4,6, Jason T Smith7, Marien Ochoa7, Xavier Intes7, Nicholas J Durr3,4.   

Abstract

This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical optics and includes microscopy, fluorescence lifetime imaging, in vivo microscopy, widefield endoscopy, optical coherence tomography, photoacoustic imaging, diffuse tomography, and functional optical brain imaging. For each of these domains, we summarize how deep learning has been applied and highlight methods by which deep learning can enable new capabilities for optics in medicine. Challenges and opportunities to improve translation and adoption of deep learning in biomedical optics are also summarized. Lasers Surg. Med.
© 2021 Wiley Periodicals LLC. © 2021 Wiley Periodicals LLC.

Entities:  

Keywords:  biomedical optics; biophotonics; computer aided detection; deep learning; diffuse tomography; fluorescence lifetime; functional optical brain imaging; in vivo microscopy; machine learning; microscopy; optical coherence tomography; photoacoustic imaging; widefield endoscopy

Mesh:

Year:  2021        PMID: 34015146      PMCID: PMC8273152          DOI: 10.1002/lsm.23414

Source DB:  PubMed          Journal:  Lasers Surg Med        ISSN: 0196-8092


  194 in total

1.  Investigating deep learning for fNIRS based BCI.

Authors:  Johannes Hennrich; Christian Herff; Dominic Heger; Tanja Schultz
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2015-08

2.  Probe-based confocal laser endomicroscopy.

Authors:  Michael B Wallace; Paul Fockens
Journal:  Gastroenterology       Date:  2009-03-28       Impact factor: 22.682

3.  Experimental images of heterogeneous turbid media by frequency-domain diffusing-photon tomography.

Authors:  M A O'Leary; D A Boas; B Chance; A G Yodh
Journal:  Opt Lett       Date:  1995-03-01       Impact factor: 3.776

4.  Deep learning model for ultrafast multifrequency optical property extractions for spatial frequency domain imaging.

Authors:  Yanyu Zhao; Yue Deng; Feng Bao; Hannah Peterson; Raeef Istfan; Darren Roblyer
Journal:  Opt Lett       Date:  2018-11-15       Impact factor: 3.776

5.  Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans.

Authors:  Zaixing Mao; Atsuya Miki; Song Mei; Ying Dong; Kazuichi Maruyama; Ryo Kawasaki; Shinichi Usui; Kenji Matsushita; Kohji Nishida; Kinpui Chan
Journal:  Biomed Opt Express       Date:  2019-10-21       Impact factor: 3.732

6.  A machine learning approach to predict surgical learning curves.

Authors:  Yuanyuan Gao; Uwe Kruger; Xavier Intes; Steven Schwaitzberg; Suvranu De
Journal:  Surgery       Date:  2019-11-18       Impact factor: 3.982

7.  Explainable Anatomical Shape Analysis Through Deep Hierarchical Generative Models.

Authors:  Carlo Biffi; Juan J Cerrolaza; Giacomo Tarroni; Wenjia Bai; Antonio de Marvao; Ozan Oktay; Christian Ledig; Loic Le Folgoc; Konstantinos Kamnitsas; Georgia Doumou; Jinming Duan; Sanjay K Prasad; Stuart A Cook; Declan P O'Regan; Daniel Rueckert
Journal:  IEEE Trans Med Imaging       Date:  2020-01-06       Impact factor: 10.048

8.  Light in diagnosis, therapy and surgery.

Authors:  Seok Hyun Yun; Sheldon J J Kwok
Journal:  Nat Biomed Eng       Date:  2017-01-10       Impact factor: 25.671

9.  Rapid tissue oxygenation mapping from snapshot structured-light images with adversarial deep learning.

Authors:  Mason T Chen; Nicholas J Durr
Journal:  J Biomed Opt       Date:  2020-11       Impact factor: 3.170

10.  Deep-learning-based motion-correction algorithm in optical resolution photoacoustic microscopy.

Authors:  Xingxing Chen; Weizhi Qi; Lei Xi
Journal:  Vis Comput Ind Biomed Art       Date:  2019-10-29
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  8 in total

1.  Hyperspectral evaluation of vasculature in induced peritonitis mouse models.

Authors:  Jošt Stergar; Katja Lakota; Martina Perše; Matija Tomšič; Matija Milanič
Journal:  Biomed Opt Express       Date:  2022-05-18       Impact factor: 3.562

2.  Weighted average ensemble-based semantic segmentation in biological electron microscopy images.

Authors:  Kavitha Shaga Devan; Hans A Kestler; Clarissa Read; Paul Walther
Journal:  Histochem Cell Biol       Date:  2022-08-20       Impact factor: 2.531

3.  Emerging and future use of intra-surgical volumetric X-ray imaging and adjuvant tools for decision support in breast-conserving surgery.

Authors:  Samuel S Streeter; Brady Hunt; Keith D Paulsen; Brian W Pogue
Journal:  Curr Opin Biomed Eng       Date:  2022-03-28

Review 4.  Photoacoustic imaging aided with deep learning: a review.

Authors:  Praveenbalaji Rajendran; Arunima Sharma; Manojit Pramanik
Journal:  Biomed Eng Lett       Date:  2021-11-23

Review 5.  Deep learning in macroscopic diffuse optical imaging.

Authors:  Jason T Smith; Marien Ochoa; Denzel Faulkner; Grant Haskins; Xavier Intes
Journal:  J Biomed Opt       Date:  2022-02       Impact factor: 3.758

6.  Deep learning augmented microscopy: a faster, wider view, higher resolution autofluorescence-harmonic microscopy.

Authors:  Lei Tian
Journal:  Light Sci Appl       Date:  2022-04-24       Impact factor: 20.257

Review 7.  Deep learning in fNIRS: a review.

Authors:  Condell Eastmond; Aseem Subedi; Suvranu De; Xavier Intes
Journal:  Neurophotonics       Date:  2022-07-20       Impact factor: 4.212

8.  Deep learning methods hold promise for light fluence compensation in three-dimensional optoacoustic imaging.

Authors:  Arumugaraj Madasamy; Vipul Gujrati; Vasilis Ntziachristos; Jaya Prakash
Journal:  J Biomed Opt       Date:  2022-10       Impact factor: 3.758

  8 in total

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