Wyniki wyszukiwania dla: SKIN LESIONS

• Deep neural networks approach to skin lesions classification — A comparative analysis

  Publikacja

  • A. Kwasigroch
  • A. Mikołajczyk-Bareła
  • M. Grochowski

  - Rok 2017

  The paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...

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• Optimal Selection of Input Features and an Acompanying Neural Network Structure for the Classification Purposes - Skin Lesions Case Study

  Publikacja

  • A. Mikolajczyk
  • M. Grochowski
  • A. Kwasigroch
  • A. Mikołajczyk
  • M. Grochowski

  - Rok 2018

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• Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study

  Publikacja

  • M. Grochowski
  • A. Mikołajczyk-Bareła
  • A. Kwasigroch

  - Rok 2018

  Malignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...

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• Real-Time Skin Quality Assessment System

  Publikacja

  • T. Kocejko
  • A. Krajna

  - Rok 2024

  This thesis presents a real-time skin assessment system with the main aim of detecting inflammatory acne lesions and tracking skin conditions. A facial acne lesion detection algorithm was developed, using a pre-trained YOLOv8 model for lesion detection and a Mediapipe detector for face detection. The proposed solution aims to create a system used in smart mirrors to help users self-monitor and monitor their skin condition in real...

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• Use of optical skin phantoms for preclinical evaluation of laser efficiency for skin lesion therapy

  Publikacja

  • M. Wróbel
  • M. Szczerska
  • S. Galla
  • L. Piechowski
  • M. Sawczak
  • A. P. Popov
  • A. Bykov
  • V. Tuchin
  • A. Cenian

  - JOURNAL OF BIOMEDICAL OPTICS - Rok 2015

  Skin lesions are commonly treated using laser heating. However, the introduction of new devices into clinical practice requires evaluation of their performance. This study presents the application of optical phantoms for assessment of a newly developed 975-nm pulsed diode laser system for dermatological purposes. Such phantoms closely mimic the absorption and scattering of real human skin (although not precisely in relation to...

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• Investigation of photothermolysis therapy of human skin diseases using optical phantoms

  Publikacja

  • M. Szczerska
  • M. Wróbel
  • S. Galla
  • A. P. Popov
  • A. Bykov
  • V. Tuchin
  • A. Cenian

  - Rok 2015

  Dermatological diseases, such as neurofibroma (Recklinghausen disease) or hemangiomas can be efficiently treated using photothermolysis from laser irradiation. We have utilized a developed 975 nm fiber diode laser as a low-cost alternative over common Nd:YAG lasers. This paper describes the investigations of interaction of 975 nm diode laser radiation-pulses with optical skin phantoms which were designed and manufactured in our...

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• Intelligent system supporting diagnosis of malignant melanoma

  Publikacja

  • A. Mikołajczyk-Bareła
  • A. Kwasigroch
  • M. Grochowski

  - Rok 2017

  Malignant melanomas are the most deadly type of skin cancers. Early diagnosis is a key for successful treatment and survival. The paper presents the system for supporting the process of diagnosis of skin lesions in order to detect a malignant melanoma. The paper describes the development process of an intel-ligent system purposed for the diagnosis of malignant melanoma. Presented sys-tem can be used as a decision support system...

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• DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES

  Publikacja

  • M. Grochowski
  • A. Mikołajczyk-Bareła
  • A. Kwasigroch

  - Metrology and Measurement Systems - Rok 2019

  Malignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...

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• Melanoma skin cancer detection using mask-RCNN with modified GRU model

  Publikacja

  • K. M. Monica
  • J. Shreeharsha
  • P. Falkowski-Gilski
  • B. Falkowska-Gilska
  • M. Awasthy
  • R. Phadk

  - Frontiers in Physiology - Rok 2024

  Introduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...

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• DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY

  Publikacja

  • A. Kwasigroch
  • A. Mikołajczyk-Bareła
  • M. Grochowski

  - Rok 2017

  The paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...

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• SkinDepth - synthetic 3D skin lesion database

  Dane Badawcze

  wersja 1.0 open access

  • A. Jezierska
  • M. Woźniak

  SkinDepth is the first synthetic 3D skin lesion database. The release of SkinDepth dataset intends to contribute to the development of algorithms for:

• Selected Technical Issues of Deep Neural Networks for Image Classification Purposes

  Publikacja

  • M. Grochowski
  • A. Kwasigroch
  • A. Mikołajczyk-Bareła

  - Bulletin of the Polish Academy of Sciences-Technical Sciences - Rok 2019

  In recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...

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• Kaposi sarcoma - Male, 85 - Tissue image [6170729592672621]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Pemphigoid - Female, 58 - Tissue image [6160730013049181]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Pemphigus - Male, 72 - Tissue image [10190730005921281]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Adnexal tumor, benign - Male, 48 - Tissue image [3300730069443171]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Malignant melanoma, NOS - Female, 79 - Tissue image [6060730023675981]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Intradermal nevus - Female, 36 - Tissue image [6170730026743251]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of VULVA tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 85 - Tissue image [6170730026738511]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 85 - Tissue image [5240730013786181]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 85 - Tissue image [5240730013784711]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Pemphigoid - Female, 68 - Tissue image [12040630008877661]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Anogenital (venereal) warts - Female, 29 - Tissue image [6190730017336521]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of VULVA tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Anogenital (venereal) warts - Female, 63 - Tissue image [6060730023679791]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of VULVA tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Anogenital (venereal) warts - Female, 22 - Tissue image [6170730026746981]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of VULVA tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Anogenital (venereal) warts - Female, 37 - Tissue image [6170730026745601]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of VULVA tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 40 - Tissue image [5240730013785661]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 35 - Tissue image [5240730013797071]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 35 - Tissue image [5240730013797841]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 35 - Tissue image [9080730005565271]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 35 - Tissue image [524073001379791]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 40 - Tissue image [5240730013782711]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 40 - Tissue image [5240730013782391]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 40 - Tissue image [6170730026737151]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 40 - Tissue image [5240730013782561]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 35 - Tissue image [524073001379851]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia

  Publikacja

  • A. Kwasigroch

  - Rok 2024

  W pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...

  Pełny tekst do pobrania w portalu

• Molluscum contagiosum - Female, 46 - Tissue image [7120729593136881]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of VULVA tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 44 - Tissue image [6170730026735261]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 44 - Tissue image [5240730013787511]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 44 - Tissue image [524073001378841]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 44 - Tissue image [5240730013788871]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

• Kaposi sarcoma - Male, 44 - Tissue image [5240730013789231]

  Dane Badawcze

  open access

  • Gdański Uniwersytet Medyczny

  This is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.