Influence of evaluation of clinical pictures on the histopathologic diagnosis of inflammatory skin disorders

Cerroni, Lorenzo; Argényi, Zsolt B.; Cerio, R.; Facchetti, Fabio; Kittler, Harald; Kutzner, Heinz; Requena, Luis; Sangüeza, Omar P.; Smoller, Bruce R.; Wechsler, Janine; Kerl, Helmut

doi:10.1016/j.jaad.2009.09.009

Cited by 35 publications

(32 citation statements)

References 18 publications

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“…Diagnoses from clinicians may reduce the number of differential diagnoses by pathologists. In previous reports, 13,14 the diagnostic accuracy rate has been shown to be increased when the clinical pictures or clinical information are provided to pathologists. In our study, the clinicopathological consistency was 72.6% for seborrheic keratosis and 88% for benign melanocytic nevus.…”

Section: Discussionmentioning

confidence: 98%

Clinicopathological consistency in skin disorders: A retrospective study of 3949 pathological reports

Aslan

Göktay

Mansur

et al. 2012

Journal of the American Academy of Dermatology

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Section: Discussionmentioning

confidence: 98%

Clinicopathological consistency in skin disorders: A retrospective study of 3949 pathological reports

Aslan

Göktay

Mansur

et al. 2012

Journal of the American Academy of Dermatology

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“…1 However, what has been learned over the years is that dermatopathology is macroscopic and microscopic pathology of the skin, and that evaluation of clinical presentation represents a crucial step in the diagnostic process. 7,8 For more than twenty years, molecular biology has been developed in many medical fields. It has proven to be a great asset in understanding o f m e c h a n i s m s o f d i s e a s e a n d at a diagnostic level it has proven to be a great tool.…”

Section: Introductionmentioning

confidence: 99%

Pediatric dermatopathology: an overview

2017

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Dermatopathology is a subspecialty of pathology and dermatology involving correlation of clinical information with microscopic observations of skin biopsies to provide diagnostic information. Pediatric dermatology is a subspecialty of dermatology for which specific points need to be known for evaluating and managing skin disorders in children. The histopathological approach and other important factors for definitive diagnoses in pediatric dermatopathology are reviewed. Skin diseases in children are not necessarily smaller versions of those that develop in adults and some diaseases may be confined to pediatric age group. An experienced team of dermatology and pathology increases the success of skin biopsies in pediatric dermatology besides the excellent technical skills. The histopathologic findings of skin lesions in children should be evaluated by pediatric pathologists, who have a specific interest for pediatric dermatopathology, in close collaboration with pediatric dermatologists.

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“…On the other hand, since it performs per block wavelet transformation, blank blocks can be easily discarded so as to get more precise representations for irregular regions. We regard this feature extraction method potentially close to the intuition presented in many famous dermatology literatures [7][8] [9].…”

Section: B Region Feature Extractionmentioning

confidence: 61%

“…In general, the diagnosis of skin disease is divided into two steps [7]. The first step is skin surface inspecting.…”

Section: Introductionmentioning

confidence: 99%

Multi-instance learning for skin biopsy image features recognition

Zhang

Shu

Liang

et al. 2012

2012 IEEE International Conference on Bioinformatics and Biomedicine

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In this paper, a multi-instance learning framework is introduced to solve the problem of skin biopsy image features recognition. Previously reported methods for skin surface images were mostly based on color features extraction. They are incapable to be directly applied to skin biopsy image features recognition because biopsy images are often dyed and have obvious inner structures with different textures. Therefore, we regard skin biopsy images as multi-instance samples, whose instances are regions or structures captured by applying Normalized Cut. Texture feature extraction methods are used to express each region as a vectorial expression. Then two multi-instance learning algorithms reported successful in various image retrieval tasks were applied. Nine features were manually selected as target features to evaluate the proposed method on a skin disease diagnosis datasets of 6579 biopsy images from 2010 to 2011. The result showed that the proposed method is effective and medically acceptable.

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Influence of evaluation of clinical pictures on the histopathologic diagnosis of inflammatory skin disorders

Cited by 35 publications

References 18 publications

Clinicopathological consistency in skin disorders: A retrospective study of 3949 pathological reports

Clinicopathological consistency in skin disorders: A retrospective study of 3949 pathological reports

Pediatric dermatopathology: an overview

Multi-instance learning for skin biopsy image features recognition

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