Breast cancer detection using deep learning technique
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Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Altınbaş Üniversitesi / Lisansüstü Eğitim Enstitüsü
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Breast cancer has become the most common form of cancer in world recently having overtaken
cervical cancer in urban cities. Immense research has been carried out on breast cancer and several automated machines for detection have been formed, however, they are far from perfection and
medical assessments need more reliable services. Computer Assisted Diagnostics (CAD) programs
have been developed over the past two decades to help radiologists interpret mammogram
screening. Deep convolutionary neural networks (CNN), which have surpassed human output
since 2012, have been an immense success in image recognition. Deep CNNs will revolutionize
the analysis of medical images. We propose a method for breast cancer detection based on Faster
R-CNN, The most common frameworks for object detection. In a non-human interference
mammogram, the device detects and categorizes malignant or benign lesions. The method
proposed sets the current status of the INbreast database public classification scheme, AUC = 0.95.
In the digital mammography challenge DREAM with 0.85 = 0.85, the method mentioned here was
second. When the device is used as a sensor, the accuracy of the INbreast data set is extremely low
with very false positive image points.
Açıklama
Anahtar Kelimeler
Convolutional Neural Networks, Deep Learning, Mammography, Breast Cancer Screening, Breast Density
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Alkurdi, Dunya Ahmed. (2020). Breast cancer detection using deep learning technique. (Yayınlanmamış yüksek lisans tezi). Altınbaş Üniversitesi, Lisansüstü Eğitim Enstitüsü, İstanbul.
