Kernel Fisher Discriminant and Elliptic Shape Model for Automatic Measurement of Allergic Reactions

Huttunen, Heikki; Ryynänen, Jari-Pekka; Forsvik, Heikki; Voipio, Ville; Kikuchi, Hisakazu

doi:10.1007/978-3-642-21227-7_71

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…Semiautomatic measurements are useful for different kinds of allergic reactions that need to be visually detected and classified. Huttunen et al [27] also proposed segmentation where user has to point the position of an allergic rash.…”

Section: Supervised Visual System For Recognition Of Erythema Migransmentioning

confidence: 99%

Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis

Čuk¹,

Gams²,

Mozek³

et al. 2014

SV-JME

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Lyme borreliosis is the most common human tick-borne infectious disease in the northern hemisphere, occurring predominantly in temperate regions of North America, Europe and Asia. The disease's most frequent manifestation is erythema migrans, a skin lesion that appears within days to weeks of a tick bite. Early recognition of the lesion is important since it enables proper management and thus prevention of later consequences of the disease which can hamper normal life. In this article, a novel visual system for recognition of erythema migrans is presented based on new multimedia interactive terminal technology available also on smartphones. For potential erythema migrans skin lesion edge detection, we compared three different methods: GrowCut, maximal similarity based region merging and random walker segmentation method. The results obtained with GrowCut method are better than those obtained with random walker method. The GrowCut method, improved with our new finger draw (FD1) marker yields comparable results to those obtained with maximal similarity based region merging method. Several classification algorithms including naive Bayes, support vector machine, AdaBoost, random forest, and neural network were compared and used for classification of skin lesions into ellipse, the most common shape of erythema migrans and erythema migrans class.

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Section: Supervised Visual System For Recognition Of Erythema Migransmentioning

confidence: 99%

Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis

Čuk¹,

Gams²,

Mozek³

et al. 2014

SV-JME

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“…However, the visual interpretation of these images produces a significant amount of variation [12]. Even assessing the images through digital image processing programs is not entirely reliable and has not been sufficiently studied on different skin tones [13, 14].…”

Section: Introductionmentioning

confidence: 99%

Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting

Pineda¹,

Vargas²,

Romero³

et al. 2019

PLoS ONE

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The conventional reading of the skin prick test (SPT) for diagnosing allergies is prone to inter- and intra-observer variations. Drawing the contours of the skin wheals from the SPT and scanning them for computer processing is cumbersome. However, 3D scanning technology promises the best results in terms of accuracy, fast acquisition, and processing. In this work, we present a wide-field 3D imaging system for the 3D reconstruction of the SPT, and we propose an automated method for the measurement of the skin wheals. The automated measurement is based on pyramidal decomposition and parametric 3D surface fitting for estimating the sizes of the wheals directly. We proposed two parametric models for the diameter estimation. Model 1 is based on an inverted Elliptical Paraboloid function, and model 2 on a super-Gaussian function. The accuracy of the 3D imaging system was evaluated with validation objects obtaining transversal and depth accuracies within ± 0.1 mm and ± 0.01 mm, respectively. We tested the method on 80 SPTs conducted in volunteer subjects, which resulted in 61 detected wheals. We analyzed the accuracy of the models against manual reference measurements from a physician and obtained that the parametric model 2 on average yields diameters closer to the reference measurements (model 1: -0.398 mm vs. model 2: -0.339 mm) with narrower 95% limits of agreement (model 1: [-1.58, 0.78] mm vs. model 2: [-1.39, 0.71] mm) in a Bland-Altman analysis. In one subject, we tested the reproducibility of the method by registering the forearm under five different poses obtaining a maximum coefficient of variation of 5.24% in the estimated wheal diameters. The proposed method delivers accurate and reproducible measurements of the SPT.

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“…This chapter is organized so that section 2 discusses the effect of the imaging hardware and camera settings on the medical and scientific imaging. After that we present our algorithm for segmenting the wheal area in Section 3, which is based on our earlier paper (Huttunen et al, 2011). Finally, Section 4 discusses the results.…”

Section: Introductionmentioning

confidence: 99%

Practical Imaging in Dermatology

Voipio¹,

Huttunen²,

Forsvik³

2012

Digital Image Processing

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Kernel Fisher Discriminant and Elliptic Shape Model for Automatic Measurement of Allergic Reactions

Cited by 5 publications

References 10 publications

Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis

Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis

Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting

Practical Imaging in Dermatology

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