ArticleDiagnostics (Basel, Switzerland)2020
Diagnostics of Melanocytic Skin Tumours by a Combination of Ultrasonic, Dermatoscopic and Spectrophotometric Image Parameters.
Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Raman spectral band imaging for the diagnostics and classification of canine and feline cutaneous tumors.The veterinary quarterly · 2025Article
- Machine learning based diagnostics of veterinary cancer on ultrasound and optical imaging data.The veterinary quarterly · 2025Article
- Differentiation of canine and feline neoplasms using multi-modal imaging and machine learning.Scientific reports · 2025Article
- The usefulness of automated high frequency ultrasound image analysis in atopic dermatitis staging.Scientific reports · 2025Article
- Radiation-induced skin injury: a review of pathophysiology, assessment, management, and re-irradiation protocols.Frontiers in oncology · 2025Review
- Automatic Assessment of AK Stage Based on Dermatoscopic and HFUS Imaging-A Preliminary Study.Journal of clinical medicine · 2024Article
- Computer-Aided Diagnosis Methods for High-Frequency Ultrasound Data Analysis: A Review.Sensors (Basel, Switzerland) · 2022Review
- Preliminary Clinical Experience with a Novel Optical-Ultrasound Imaging Device on Various Skin Lesions.Diagnostics (Basel, Switzerland) · 2022Article
- Automated Skin Lesion Classification on Ultrasound Images.Diagnostics (Basel, Switzerland) · 2021Article
- Investigating Serum and Tissue Expression Identified a Cytokine/Chemokine Signature as a Highly Effective Melanoma Marker.Cancers · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Dermatoscopy, high-frequency ultrasonography (HFUS) and spectrophotometry are promising quantitative imaging techniques for the investigation and diagnostics of cutaneous melanocytic tumors. In this paper, we propose the hybrid technique and automatic prognostic models by combining the quantitative image parameters of ultrasonic B-scan images, dermatoscopic and spectrophotometric images (melanin, blood and collagen) to increase accuracy in the diagnostics of cutaneous melanoma. The extracted sets of various quantitative parameters and features of dermatoscopic, ultrasonic and spectrometric images were used to develop the four different classification models: logistic regression (LR), linear discriminant analysis (LDA), support vector machine (SVM) and Naive Bayes. The results were compared to the combination of only two techniques out of three. The reliable differentiation between melanocytic naevus and melanoma were achieved by the proposed technique. The accuracy of more than 90% was estimated in the case of LR, LDA and SVM by the proposed method.
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Registered trials
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