Application of Acousto-Optical Hyperspectral Imaging for Skin Cancer Diagnostics

Пожар, В. Э.; Мачихин, А. С.; Myakinin, Oleg O.; Bratchenko, Ivan А.

doi:10.1007/978-3-030-44594-2_14

Cited by 2 publications

(6 citation statements)

References 77 publications

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“…Patient Selection Index Test Referen Standa Leon et al [136] Lindholm et al [137] Christensen et al [138] Hosking et al [139] Pozhar et al [140] Pardo et al [141] Vinokurov et al [142] Rasanen et al [143] T. Nagaoka et al [144] Zherdeva et al [145] Low Risk;…”

Section: Studymentioning

confidence: 99%

“…Furthermore, the assessment included considerations pertaining to the suitability of the study population, the performance of the diagnostic test under investigation, and the established benchmark against which it was compared. [136] dholm et al [137] istensen et al [138] osking et al [139] ozhar et al [140] ardo et al [141] okurov et al [142] sanen et al [143] agaoka et al [144] erdeva et al [145] Low Risk;…”

Section: Studies Under Clinical Feature Observationmentioning

confidence: 99%

“…The objective of efficacy of several CA view provides a conc the objectives, the us grouping and meta-a and AUC values ass This study primarily corresponding literat comparison utilizing Leon et al used cancer, with the ob Pozhar et al [140] formed decision-making.…”

Section: Studies Under Clinmentioning

confidence: 99%

“…Leon et al [136] Lindholm et al[137] Christensen et al[138] Hosking et al[139] Pozhar et al[140] Pardo et al[141] …”

mentioning

confidence: 99%

“…Hosking et al[139] Pozhar et al[140] Pardo et al[141] Vinokurov et al[142] Rasanen et al[143] T. Nagaoka et al[144] Zherdeva et al[145] …”

mentioning

confidence: 99%

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A Review of Recent Advances in Computer-Aided Detection Methods Using Hyperspectral Imaging Engineering to Detect Skin Cancer

Huang,

Hsiao,

Karmakar

et al. 2023

Cancers

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Skin cancer, a malignant neoplasm originating from skin cell types including keratinocytes, melanocytes, and sweat glands, comprises three primary forms: basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and malignant melanoma (MM). BCC and SCC, while constituting the most prevalent categories of skin cancer, are generally considered less aggressive compared to MM. Notably, MM possesses a greater capacity for invasiveness, enabling infiltration into adjacent tissues and dissemination via both the circulatory and lymphatic systems. Risk factors associated with skin cancer encompass ultraviolet (UV) radiation exposure, fair skin complexion, a history of sunburn incidents, genetic predisposition, immunosuppressive conditions, and exposure to environmental carcinogens. Early detection of skin cancer is of paramount importance to optimize treatment outcomes and preclude the progression of disease, either locally or to distant sites. In pursuit of this objective, numerous computer-aided diagnosis (CAD) systems have been developed. Hyperspectral imaging (HSI), distinguished by its capacity to capture information spanning the electromagnetic spectrum, surpasses conventional RGB imaging, which relies solely on three color channels. Consequently, this study offers a comprehensive exploration of recent CAD investigations pertaining to skin cancer detection and diagnosis utilizing HSI, emphasizing diagnostic performance parameters such as sensitivity and specificity.

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Section: Studymentioning

confidence: 99%

Section: Studies Under Clinical Feature Observationmentioning

confidence: 99%

Section: Studies Under Clinmentioning

confidence: 99%

“…Leon et al [136] Lindholm et al[137] Christensen et al[138] Hosking et al[139] Pozhar et al[140] Pardo et al[141] …”

mentioning

confidence: 99%

“…Hosking et al[139] Pozhar et al[140] Pardo et al[141] Vinokurov et al[142] Rasanen et al[143] T. Nagaoka et al[144] Zherdeva et al[145] …”

mentioning

confidence: 99%

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A Review of Recent Advances in Computer-Aided Detection Methods Using Hyperspectral Imaging Engineering to Detect Skin Cancer

Huang,

Hsiao,

Karmakar

et al. 2023

Cancers

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Raman spectroscopy in noninvasive optical diagnostics of skin neoplasms

Kaganov,

Loginova,

Moryatov

et al. 2023

Science and Innovations in Medicine

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Aim to propose a schematic design of a new prototype having a potential for mass production and use in medical institutions for routine diagnostics of skin neoplasms. Material and methods. The study included more than 600 patients with various skin neoplasms. We studied the samples of various skin neoplasms obtained after surgical treatment in the departments of the Samara Regional Clinical Oncology Center. For this purpose, we used the proposed original experimental device for Raman laser spectroscopy. The received signal was processed with a designed algorithm using artificial intelligence. Results. The proposed diagnostic method reached the 89% sensitivity and 93% specificity proving to be effective. As a result, we have substantiated the technological possibility of creating a portable cost-saving spectroscopic technique with a neural network classifier. The device allows to perform preliminary diagnostics without the involvement of a specialist doctor and is devoid of subjective analysis criteria.

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Application of Acousto-Optical Hyperspectral Imaging for Skin Cancer Diagnostics

Cited by 2 publications

References 77 publications

A Review of Recent Advances in Computer-Aided Detection Methods Using Hyperspectral Imaging Engineering to Detect Skin Cancer

A Review of Recent Advances in Computer-Aided Detection Methods Using Hyperspectral Imaging Engineering to Detect Skin Cancer

Raman spectroscopy in noninvasive optical diagnostics of skin neoplasms

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