Application of Multispectral Imaging in the Human Tympanic Membrane

Tien, Tran Van; Thao, Mi Lu Thi; Quynh, Linh Bui Mai; Khuong, Cat Phan Ngoc; Quang, Linh Huynh

doi:10.1155/2020/6219845

Cited by 4 publications

(4 citation statements)

References 21 publications

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“…A variety of imaging techniques extending beyond the visible light spectrum have shown promise in identifying middle ear pathology. Otoscopy using multi-color reflectance can offer improved assessment of middle ear structures and the tympanic membrane 34 , 48 . Fluorescent otoscopy can highlight the presence of cholesteatoma with the potential to guide resection attempts in the future 49 .…”

Section: Discussionmentioning

confidence: 99%

Shortwave infrared otoscopy for diagnosis of middle ear effusions: a machine-learning-based approach

Kashani

Młyńczak

Zarabanda

et al. 2021

Sci Rep

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Otitis media, a common disease marked by the presence of fluid within the middle ear space, imparts a significant global health and economic burden. Identifying an effusion through the tympanic membrane is critical to diagnostic success but remains challenging due to the inherent limitations of visible light otoscopy and user interpretation. Here we describe a powerful diagnostic approach to otitis media utilizing advancements in otoscopy and machine learning. We developed an otoscope that visualizes middle ear structures and fluid in the shortwave infrared region, holding several advantages over traditional approaches. Images were captured in vivo and then processed by a novel machine learning based algorithm. The model predicts the presence of effusions with greater accuracy than current techniques, offering specificity and sensitivity over 90%. This platform has the potential to reduce costs and resources associated with otitis media, especially as improvements are made in shortwave imaging and machine learning.

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Section: Discussionmentioning

confidence: 99%

Shortwave infrared otoscopy for diagnosis of middle ear effusions: a machine-learning-based approach

Kashani

Młyńczak

Zarabanda

et al. 2021

Sci Rep

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“…Multicolor or multispectral autofluorescence imaging [16][17][18][19] SWIR imaging [12] OCT [20,21] Otitis media DRS [22] SWIR [23,24] OCT [25][26][27][28][29] Multimodal [30] 2. Label-Free Optical Techniques 2.1.…”

Section: Tissue Differentiation and Visualization Of Tympanic Membranementioning

confidence: 99%

“…Additionally, Tran Van et al applied multispectral imaging to a cohort of 12 healthy volunteers and found that red-light images, compared with blue-, green-, and white-light images, provided the best contrast to visualize the borders of the tympanic membrane [18]. Wisotzky et al introduced a multispectral imaging system combined with an endoscope that could switch between narrow-band spectral and broad-band white illuminations.…”

Section: Tissue Differentiation and Visualization Of Tympanic Membranementioning

confidence: 99%

“…However, more research on the optimization of the best set of illimitation wavelengths for each different pathology and larger clinical studies with larger patient populations are needed for the diagnosis of different pathologies before clinical application [16,17]. Additionally, Tran Van et al applied multispectral imaging to a cohort of 12 healthy volunteers and found that red-light images, compared with blue-, green-, and white-light images, provided the best contrast to visualize the borders of the tympanic membrane [18]. Wisotzky et al introduced a multispectral imaging system combined with an endoscope that could switch between narrow-band spectral and broad-band white illuminations.…”

Section: Tissue Differentiation and Visualization Of Tympanic Membranementioning

confidence: 99%

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Label-Free Optical Technologies for Middle-Ear Diseases

Zhou,

Pandey,

Valdez

2024

Bioengineering

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Medical applications of optical technology have increased tremendously in recent decades. Label-free techniques have the unique advantage of investigating biological samples in vivo without introducing exogenous agents. This is especially beneficial for a rapid clinical translation as it reduces the need for toxicity studies and regulatory approval for exogenous labels. Emerging applications have utilized label-free optical technology for screening, diagnosis, and surgical guidance. Advancements in detection technology and rapid improvements in artificial intelligence have expedited the clinical implementation of some optical technologies. Among numerous biomedical application areas, middle-ear disease is a unique space where label-free technology has great potential. The middle ear has a unique anatomical location that can be accessed through a dark channel, the external auditory canal; it can be sampled through a tympanic membrane of approximately 100 microns in thickness. The tympanic membrane is the only membrane in the body that is surrounded by air on both sides, under normal conditions. Despite these favorable characteristics, current examination modalities for middle-ear space utilize century-old technology such as white-light otoscopy. This paper reviews existing label-free imaging technologies and their current progress in visualizing middle-ear diseases. We discuss potential opportunities, barriers, and practical considerations when transitioning label-free technology to clinical applications.

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Intelligent Control Techniques for the Detection of Biomedical Ear Infections

Abdulaal

Mehedi

Aljohani

et al. 2022

Computational Intelligence and Neuroscience

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The capacity to carry out one’s regular tasks is affected to varying degrees by hearing difficulties. Poorer understanding, slower learning, and an overall reduction in efficiency in academic endeavours are just a few of the negative impacts of hearing impairments on children’s performance, which may range from mild to severe. A significant factor in determining whether or not there will be a decrease in performance is the kind and source of impairment. Research has shown that the Artificial Neural Network technique is capable of modelling both linear and nonlinear solution surfaces in a trustworthy way, as demonstrated in previous studies. To improve the precision with which hearing impairment challenges are diagnosed, a neural network backpropagation approach has been developed with the purpose of fine-tuning the diagnostic process. In particular, it highlights the vital role performed by medical informatics in supporting doctors in the identification of diseases as well as the formulation of suitable choices via the use of data management and knowledge discovery. As part of the intelligent control method, it is proposed in this research to construct a Histogram Equalization (HE)-based Adaptive Center-Weighted Median (ACWM) filter, which is then used to segment/detect the OM in tympanic membrane images using different segmentation methods in order to minimise noise and improve the image quality. A tympanic membrane dataset, which is freely accessible, was used in all experiments.

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Application of Multispectral Imaging in the Human Tympanic Membrane

Cited by 4 publications

References 21 publications

Shortwave infrared otoscopy for diagnosis of middle ear effusions: a machine-learning-based approach

Shortwave infrared otoscopy for diagnosis of middle ear effusions: a machine-learning-based approach

Label-Free Optical Technologies for Middle-Ear Diseases

Intelligent Control Techniques for the Detection of Biomedical Ear Infections

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