Computer Aided Evaluation (CAE) of Morphologic Changes in Pigmented Skin Lesions

Rízzí, María; D’Aloia, Matteo; Cice, Gianpaolo

doi:10.1007/978-3-319-23222-5_31

Cited by 12 publications

(5 citation statements)

References 13 publications

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“…Computer aided diagnosis (CADx) of melanoma ( Figure 1 ) makes an objective evaluation of skin lesions and provides reproducible diagnosis by eliminating the inter and intra-observer variabilities typical of the examination by specialist [ 1 ]. In this perspective, the aim of CADx systems is to increase clinician performance by helping in the early identification and localization of potential abnormalities [ 2 ]. Therefore CADx system operates as an automated second opinion or as a double reading system that supports dermatologists in early assessment of skin cancer and in the follow-up of pigmented skin lesions [ 3 ].…”

Section: Overviewmentioning

confidence: 99%

Simple and Accurate Border Detection Algorithm for Melanoma Computer Aided Diagnosis

Guaragnella

Rízzí

2020

Diagnostics

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The interest of the scientific community for computer aided skin lesion analysis and characterization has been increased during the last years for the growing incidence of melanoma among cancerous pathologies. The detection of melanoma in its early stage is essential for prognosis improvement and for guaranteeing a high five-year relative survival rate of patients. The clinical diagnosis of skin lesions is challenging and not trivial since it depends on human vision and physician experience and expertise. Therefore, a computer method that makes an accurate extraction of important details of skin lesion image can assist dermatologists in cancer detection. In particular, the border detection is a critical computer vision issue owing to the wide range of lesion shapes, sizes, colours and skin texture types. In this paper, an automatic and effective pigmented skin lesion segmentation method in dermoscopic image is presented. The proposed procedure is adopted to extract a mask of the lesion region without the adoption of other signal processing procedures for image improvement. A quantitative experimental evaluation has been performed on a publicly available database. The achieved results show the method validity and its high robustness towards irregular boundaries, smooth transition between lesion and skin, noise and artifact presence.

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Section: Overviewmentioning

confidence: 99%

Simple and Accurate Border Detection Algorithm for Melanoma Computer Aided Diagnosis

Guaragnella

Rízzí

2020

Diagnostics

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“…Specificity (Sp) represents the probability of obtaining a negative HR-ECG record when VLP is not present. Accuracy (Ac) is defined as the observed agreement between the procedure results and the physicians opinion about the HR-ECG record under test [30]. They were computed as follows:…”

Section: Evaluation Parametersmentioning

confidence: 99%

Marginal Component Analysis of ECG Signals for Beat-to-Beat Detection of Ventricular Late Potentials

2019

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Heart condition diagnosis based on electrocardiogram signal analysis is the basic method used in prevention of cardiovascular diseases, which are recognized as the leading cause of death globally. To anticipate the occurrence of ventricular arrhythmia, the detection of Ventricular Late Potentials (VLPs) is clinically worthwhile. VLPs are low-amplitude and high-frequency signals appearing at the end part of QRS complexes in the electrocardiogram, which can be considered as a robust feature for arrhythmia risk stratification in patients with cardiac diseases. This paper proposes a beat-to-beat VLP detection method based on the the marginal component analysis and investigates its performance taking into account different ratios between QRS and VLP power. After a denoising phase, performed adopting the singular vector decomposition technique, heartbeats characterized by VLP onsets are identified and extracted taking into account the vector magnitude of each high resolution ECG (HR-ECG) record. To evaluate the proposed method performance, a 15-lead HR-ECG database consisting of real VLP-negative and simulated VLP-positive patterns was used. The achieved results highlight the method validity for VLP detection.

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“…Different algorithms have been proposed in the literature for a more objective diagnosis of skin lesions. They rely on identifying various features, and they classify the lesion's nature according to feature occurrence or non-occurrence [14][15][16]. Some of them aid decision making by calculating a score (such as the ABCD/ABCDE rule and the sevenpoint checklist), while others adopt qualitative criteria (such as the Menzies method) [17].…”

Section: Introductionmentioning

confidence: 99%

A Decision Support System for Melanoma Diagnosis from Dermoscopic Images

Rízzí

Guaragnella

2022

Applied Sciences

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Innovative technologies in dermatology allow for the early screening of skin cancer, which results in a reduction in the mortality rate and surgical treatments. The diagnosis of melanoma is complex not only because of the number of different lesions but because of the high similarity amongst skin lesions of different nature; hence, human vision and physician experience still play a major role. The adoption of automatic systems would aid clinical assessment and make the diagnosis reproducible by eliminating inter- and intra-observer variabilities. In our paper, we describe a computer-aided system for the early diagnosis of melanoma in dermoscopic images. A soft pre-processing phase is performed so as to avoid the loss of details both in texture, colors, and contours, and color-based image segmentation is later carried out using k-means. Features linked to both geometric properties and color characteristics are used to analyze skin lesions through a support vector machine classifier. The PH2 public database is used for the assessment of the procedure’s sensitivity, specificity, and accuracy. A statistical approach is carried out to establish the impact of image quality on performance. The obtained results show remarkable achievements, so our computer-aided approach should be suitable as a Decision Support System for melanoma detection.

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Computer Aided Evaluation (CAE) of Morphologic Changes in Pigmented Skin Lesions

Cited by 12 publications

References 13 publications

Simple and Accurate Border Detection Algorithm for Melanoma Computer Aided Diagnosis

Simple and Accurate Border Detection Algorithm for Melanoma Computer Aided Diagnosis

Marginal Component Analysis of ECG Signals for Beat-to-Beat Detection of Ventricular Late Potentials

A Decision Support System for Melanoma Diagnosis from Dermoscopic Images

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