Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques
المؤلفون المشاركون
Chang, Yung-Chieh
Huang, Po-Wen
Chang, Yu-Tzu
Chang, Ruey-Feng
Chai, Jyh-Wen
Chen, Clayton Chi-Chang
Chen, Hsian-Min
Chang, Chein-I.
Lin, Chin-Yao
Chan, Siwa
Ouyang, Yen-Chieh
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-07-28
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
Breast cancer is a main cause of disease and death for women globally.
Because of the limitations of traditional mammography and ultrasonography, magnetic resonance imaging (MRI) has gradually become an important radiological method for breast cancer assessment over the past decades.
MRI is free of the problems related to radiation exposure and provides excellent image resolution and contrast.
However, a disadvantage is the injection of contrast agent, which is toxic for some patients (such as patients with chronic renal disease or pregnant and lactating women).
Recent findings of gadolinium deposits in the brain are also a concern.
To address these issues, this paper develops an intravoxel incoherent motion- (IVIM-) MRI-based histogram analysis approach, which takes advantage of several hyperspectral techniques, such as the band expansion process (BEP), to expand a multispectral image to hyperspectral images and create an automatic target generation process (ATGP).
After automatically finding suspected targets, further detection was attained by using kernel constrained energy minimization (KCEM).
A decision tree and histogram analysis were applied to classify breast tissue via quantitative analysis for detected lesions, which were used to distinguish between three categories of breast tissue: malignant tumors (i.e., central and peripheral zone), cysts, and normal breast tissues.
The experimental results demonstrated that the proposed IVIM-MRI-based histogram analysis approach can effectively differentiate between these three breast tissue types.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chan, Siwa& Chang, Yung-Chieh& Huang, Po-Wen& Ouyang, Yen-Chieh& Chang, Yu-Tzu& Chang, Ruey-Feng…[et al.]. 2019. Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques. BioMed Research International،Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1124872
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chan, Siwa…[et al.]. Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques. BioMed Research International No. 2019 (2019), pp.1-15.
https://search.emarefa.net/detail/BIM-1124872
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chan, Siwa& Chang, Yung-Chieh& Huang, Po-Wen& Ouyang, Yen-Chieh& Chang, Yu-Tzu& Chang, Ruey-Feng…[et al.]. Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques. BioMed Research International. 2019. Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1124872
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1124872
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر