Literature DB >> 29552415

Detecting brain tumor in pathological slides using hyperspectral imaging.

Samuel Ortega1, Himar Fabelo1, Rafael Camacho2, María de la Luz Plaza2, Gustavo M Callicó1, Roberto Sarmiento1.   

Abstract

Hyperspectral imaging (HSI) is an emerging technology for medical diagnosis. This research work presents a proof-of-concept on the use of HSI data to automatically detect human brain tumor tissue in pathological slides. The samples, consisting of hyperspectral cubes collected from 400 nm to 1000 nm, were acquired from ten different patients diagnosed with high-grade glioma. Based on the diagnosis provided by pathologists, a spectral library of normal and tumor tissues was created and processed using three different supervised classification algorithms. Results prove that HSI is a suitable technique to automatically detect high-grade tumors from pathological slides.

Entities:  

Keywords:  (110.4234) Multispectral and hyperspectral imaging; (170.0170) Medical optics and biotechnology; (170.4730) Optical pathology; (170.6510) Spectroscopy, tissue diagnostics; (170.6935) Tissue characterization

Year:  2018        PMID: 29552415      PMCID: PMC5854081          DOI: 10.1364/BOE.9.000818

Source DB:  PubMed          Journal:  Biomed Opt Express        ISSN: 2156-7085            Impact factor:   3.732


  17 in total

1.  Blood vessel detection and artery-vein differentiation using hyperspectral imaging.

Authors:  Hamed Akbari; Yukio Kosugi; Kazuyuki Kojima; Naofumi Tanaka
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

2.  Spectral imaging of the retina.

Authors:  D J Mordant; I Al-Abboud; G Muyo; A Gorman; A Sallam; P Ritchie; A R Harvey; A I McNaught
Journal:  Eye (Lond)       Date:  2011-03       Impact factor: 3.775

3.  Spectral-spatial feature-based neural network method for acute lymphoblastic leukemia cell identification via microscopic hyperspectral imaging technology.

Authors:  Qian Wang; Jianbiao Wang; Mei Zhou; Qingli Li; Yiting Wang
Journal:  Biomed Opt Express       Date:  2017-05-19       Impact factor: 3.732

Review 4.  The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary.

Authors:  David N Louis; Arie Perry; Guido Reifenberger; Andreas von Deimling; Dominique Figarella-Branger; Webster K Cavenee; Hiroko Ohgaki; Otmar D Wiestler; Paul Kleihues; David W Ellison
Journal:  Acta Neuropathol       Date:  2016-05-09       Impact factor: 17.088

5.  Hyperspectral imaging based method for fast characterization of kidney stone types.

Authors:  Francisco Blanco; Montserrat López-Mesas; Silvia Serranti; Giuseppe Bonifazi; Josef Havel; Manuel Valiente
Journal:  J Biomed Opt       Date:  2012-07       Impact factor: 3.170

6.  Detection and analysis of the intestinal ischemia using visible and invisible hyperspectral imaging.

Authors:  Hamed Akbari; Yukio Kosugi; Kazuyuki Kojima; Naofumi Tanaka
Journal:  IEEE Trans Biomed Eng       Date:  2010-05-10       Impact factor: 4.538

7.  Spectral-Spatial Classification Using Tensor Modeling for Cancer Detection with Hyperspectral Imaging.

Authors:  Guolan Lu; Luma Halig; Dongsheng Wang; Zhuo Georgia Chen; Baowei Fei
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2014-03-21

8.  A Minimum Spanning Forest-Based Method for Noninvasive Cancer Detection With Hyperspectral Imaging.

Authors:  Robert Pike; Guolan Lu; Dongsheng Wang; Zhuo Georgia Chen; Baowei Fei
Journal:  IEEE Trans Biomed Eng       Date:  2015-08-14       Impact factor: 4.538

9.  Tongue tumor detection in medical hyperspectral images.

Authors:  Zhi Liu; Hongjun Wang; Qingli Li
Journal:  Sensors (Basel)       Date:  2011-12-23       Impact factor: 3.576

Review 10.  The 2007 WHO classification of tumours of the central nervous system.

Authors:  David N Louis; Hiroko Ohgaki; Otmar D Wiestler; Webster K Cavenee; Peter C Burger; Anne Jouvet; Bernd W Scheithauer; Paul Kleihues
Journal:  Acta Neuropathol       Date:  2007-07-06       Impact factor: 17.088

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  15 in total

1.  Hyperspectral imaging and deep learning for the detection of breast cancer cells in digitized histological images.

Authors:  Samuel Ortega; Martin Halicek; Himar Fabelo; Raul Guerra; Carlos Lopez; Marylene Lejaune; Fred Godtliebsen; Gustavo M Callico; Baowei Fei
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2020-03-16

2.  Tissue classification of oncologic esophageal resectates based on hyperspectral data.

Authors:  Marianne Maktabi; Hannes Köhler; Margarita Ivanova; Boris Jansen-Winkeln; Jonathan Takoh; Stefan Niebisch; Sebastian M Rabe; Thomas Neumuth; Ines Gockel; Claire Chalopin
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-06-20       Impact factor: 2.924

3.  Evaluation of hyperspectral imaging (HSI) for the measurement of ischemic conditioning effects of the gastric conduit during esophagectomy.

Authors:  Hannes Köhler; Boris Jansen-Winkeln; Marianne Maktabi; Manuel Barberio; Jonathan Takoh; Nico Holfert; Yusef Moulla; Stefan Niebisch; Michele Diana; Thomas Neumuth; Sebastian M Rabe; Claire Chalopin; Andreas Melzer; Ines Gockel
Journal:  Surg Endosc       Date:  2019-01-23       Impact factor: 4.584

4.  Detection of pancreatic tumor cell nuclei via a hyperspectral analysis of pathological slides based on stain spectra.

Authors:  Masahiro Ishikawa; Chisato Okamoto; Kazuma Shinoda; Hideki Komagata; Chika Iwamoto; Kenoki Ohuchida; Makoto Hashizume; Akinobu Shimizu; Naoki Kobayashi
Journal:  Biomed Opt Express       Date:  2019-08-09       Impact factor: 3.732

5.  Label-free hyperspectral imaging and deep-learning prediction of retinal amyloid β-protein and phosphorylated tau.

Authors:  Xiaoxi Du; Yosef Koronyo; Nazanin Mirzaei; Chengshuai Yang; Dieu-Trang Fuchs; Keith L Black; Maya Koronyo-Hamaoui; Liang Gao
Journal:  PNAS Nexus       Date:  2022-08-19

6.  Most Relevant Spectral Bands Identification for Brain Cancer Detection Using Hyperspectral Imaging.

Authors:  Beatriz Martinez; Raquel Leon; Himar Fabelo; Samuel Ortega; Juan F Piñeiro; Adam Szolna; Maria Hernandez; Carlos Espino; Aruma J O'Shanahan; David Carrera; Sara Bisshopp; Coralia Sosa; Mariano Marquez; Rafael Camacho; Maria de la Luz Plaza; Jesus Morera; Gustavo M Callico
Journal:  Sensors (Basel)       Date:  2019-12-12       Impact factor: 3.576

Review 7.  Artificial Intelligence in Brain Tumour Surgery-An Emerging Paradigm.

Authors:  Simon Williams; Hugo Layard Horsfall; Jonathan P Funnell; John G Hanrahan; Danyal Z Khan; William Muirhead; Danail Stoyanov; Hani J Marcus
Journal:  Cancers (Basel)       Date:  2021-10-07       Impact factor: 6.639

8.  Deep learning-based framework for the distinction of membranous nephropathy: a new approach through hyperspectral imagery.

Authors:  Tianqi Tu; Xueling Wei; Yue Yang; Nianrong Zhang; Wei Li; Xiaowen Tu; Wenge Li
Journal:  BMC Nephrol       Date:  2021-06-19       Impact factor: 2.388

9.  Adaptive deep learning for head and neck cancer detection using hyperspectral imaging.

Authors:  Ling Ma; Guolan Lu; Dongsheng Wang; Xulei Qin; Zhuo Georgia Chen; Baowei Fei
Journal:  Vis Comput Ind Biomed Art       Date:  2019-11-21

10.  Hyperspectral Imaging for the Detection of Glioblastoma Tumor Cells in H&E Slides Using Convolutional Neural Networks.

Authors:  Samuel Ortega; Martin Halicek; Himar Fabelo; Rafael Camacho; María de la Luz Plaza; Fred Godtliebsen; Gustavo M Callicó; Baowei Fei
Journal:  Sensors (Basel)       Date:  2020-03-30       Impact factor: 3.576

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