Literature DB >> 32390328

Classification of hyperspectral endocrine tissue images using support vector machines.

Marianne Maktabi1, Hannes Köhler1, Magarita Ivanova1, Thomas Neumuth1, Nada Rayes2, Lena Seidemann2, Robert Sucher2, Boris Jansen-Winkeln2, Ines Gockel2, Manuel Barberio2,3, Claire Chalopin1.   

Abstract

BACKGROUND: Thyroidectomy is one of the most commonly performed surgical procedures. The region of the neck has a very complex structural organization. It would be beneficial to introduce a tool that can assist the surgeon in tissue discrimination during the procedure. One such solution is the noninvasive and contactless technique, called hyperspectral imaging (HSI).
METHODS: To interpret the HSI data, we implemented a supervised classification method to automatically discriminate the parathyroid, the thyroid, and the recurrent laryngeal nerve from surrounding tissue(muscle, skin) and materials (instruments, gauze). A leave-one-patient-out cross-validation was performed.
RESULTS: The best performance was obtained using support vector machine (SVM) with a classification and visualization in less than 1.4 seconds. A mean patient accuracy of 68% ± 23% was obtained for all tissues and material types.
CONCLUSIONS: The proposed method showed promising results and have to be confirmed on a larger cohort of patient data.
© 2020 The Authors. The International Journal of Medical Robotics and Computer Assisted Surgery published by John Wiley & Sons Ltd.

Entities:  

Keywords:  computer assisted surgery; head and neck; imaged guided surgery; intraoperative imaging; surgery; thyroidectomy

Year:  2020        PMID: 32390328     DOI: 10.1002/rcs.2121

Source DB:  PubMed          Journal:  Int J Med Robot        ISSN: 1478-5951            Impact factor:   2.547


  5 in total

Review 1.  [Artificial intelligence and hyperspectral imaging for image-guided assistance in minimally invasive surgery].

Authors:  Claire Chalopin; Felix Nickel; Annekatrin Pfahl; Hannes Köhler; Marianne Maktabi; René Thieme; Robert Sucher; Boris Jansen-Winkeln; Alexander Studier-Fischer; Silvia Seidlitz; Lena Maier-Hein; Thomas Neumuth; Andreas Melzer; Beat Peter Müller-Stich; Ines Gockel
Journal:  Chirurgie (Heidelb)       Date:  2022-07-07

2.  Feedforward Artificial Neural Network-Based Colorectal Cancer Detection Using Hyperspectral Imaging: A Step towards Automatic Optical Biopsy.

Authors:  Boris Jansen-Winkeln; Manuel Barberio; Claire Chalopin; Katrin Schierle; Michele Diana; Hannes Köhler; Ines Gockel; Marianne Maktabi
Journal:  Cancers (Basel)       Date:  2021-02-25       Impact factor: 6.575

3.  Feature Genes in Neuroblastoma Distinguishing High-Risk and Non-high-Risk Neuroblastoma Patients: Development and Validation Combining Random Forest With Artificial Neural Network.

Authors:  Sha Yang; Lingfeng Zeng; Xin Jin; Huapeng Lin; Jianning Song
Journal:  Front Med (Lausanne)       Date:  2022-07-15

4.  Video: Clinical evaluation of a laparoscopic hyperspectral imaging system.

Authors:  Annekatrin Pfahl; Hannes Köhler; Claire Chalopin; Ines Gockel; Madeleine T Thomaßen; Marianne Maktabi; Albrecht M Bloße; Matthias Mehdorn; Orestis Lyros; Yusef Moulla; Stefan Niebisch; Boris Jansen-Winkeln
Journal:  Surg Endosc       Date:  2022-05-11       Impact factor: 3.453

5.  Laparoscopic system for simultaneous high-resolution video and rapid hyperspectral imaging in the visible and near-infrared spectral range.

Authors:  Hannes Köhler; Axel Kulcke; Marianne Maktabi; Yusef Moulla; Boris Jansen-Winkeln; Manuel Barberio; Michele Diana; Ines Gockel; Thomas Neumuth; Claire Chalopin
Journal:  J Biomed Opt       Date:  2020-08       Impact factor: 3.170

  5 in total

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