Novel Four Stages Classification of Breast Cancer Using Infrared Thermal Imaging and a Deep Learning Model

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F19%3A50015948" target="_blank" >RIV/62690094:18450/19:50015948 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.researchgate.net/publication/332775063_Novel_Four_Stages_Classification_of_Breast_Cancer_Using_Infrared_Thermal_Imaging_and_a_Deep_Learning_Model" target="_blank" >https://www.researchgate.net/publication/332775063_Novel_Four_Stages_Classification_of_Breast_Cancer_Using_Infrared_Thermal_Imaging_and_a_Deep_Learning_Model</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-17935-9_7" target="_blank" >10.1007/978-3-030-17935-9_7</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Novel Four Stages Classification of Breast Cancer Using Infrared Thermal Imaging and a Deep Learning Model

Popis výsledku v původním jazyce

According to a recent study conducted in 2016, 2.8 million women worldwide had already been diagnosed with breast cancer; moreover, the medical care of a patient with breast cancer is costly and, given the cost and value of the preservation of the health of the citizen, the prevention of breast cancer has become a priority in public health. We have seen the apparition of several techniques during the past 60 years, such as mammography, which is frequently used for breast cancer diagnosis. However, false positives of mammography can occur in which the patient is diagnosed positive by another technique. Also, the potential side effects of using mammography may encourage patients and physicians to look for other diagnostic methods. This article, present a Novel technique based on an inceptionV3 couples to k-Nearest Neighbors (InceptionV3-KNN) and a particular module that we named: “StageCancer.” These techniques succeed to classify breast cancer in four stages (T1: non-invasive breast cancer, T2: the tumor measures up to 2 cm, T3: the tumor is larger than 5 cm and T4: the full breast is cover by cancer).

Název v anglickém jazyce

Novel Four Stages Classification of Breast Cancer Using Infrared Thermal Imaging and a Deep Learning Model

Popis výsledku anglicky

According to a recent study conducted in 2016, 2.8 million women worldwide had already been diagnosed with breast cancer; moreover, the medical care of a patient with breast cancer is costly and, given the cost and value of the preservation of the health of the citizen, the prevention of breast cancer has become a priority in public health. We have seen the apparition of several techniques during the past 60 years, such as mammography, which is frequently used for breast cancer diagnosis. However, false positives of mammography can occur in which the patient is diagnosed positive by another technique. Also, the potential side effects of using mammography may encourage patients and physicians to look for other diagnostic methods. This article, present a Novel technique based on an inceptionV3 couples to k-Nearest Neighbors (InceptionV3-KNN) and a particular module that we named: “StageCancer.” These techniques succeed to classify breast cancer in four stages (T1: non-invasive breast cancer, T2: the tumor measures up to 2 cm, T3: the tumor is larger than 5 cm and T4: the full breast is cover by cancer).

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISBN

978-3-030-17934-2

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

12

Strana od-do

63-74

Název nakladatele

Springer Verlag

Místo vydání

Berlin

Místo konání akce

Yogakarta

Datum konání akce

8. 5. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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