PhD Dissertation Defense Announcement of Yahya Alzahrani: "Convolutional Neural Networks for Breast Ultrasound Image Segmentation"

Monday, December 20, 2021 - 10:00 to 13:00


The School of Computer Science is pleased to present…  

PhD Dissertation Defense by: Yahya Alzahrani 

Date: Monday December 20th, 2021 
Time:  10:00 am – 1:00 pm 
Passcode: If interested in attending this event, contact the Graduate Secretary at with sufficient notice before the event to obtain the passcode   


Medical image segmentation of anatomical structures in various types of 2D and 3D medical images plays an important role in the early stages detection of breast cancer. Different modalities, such as Magnetic Resonance Imaging (MRI), X-Rays, Positron Emission Tomography (PET), Computed Tomography (CT), and Ultrasound (US) can be used for diagnostics, planning, and treatment.  In this dissertation, we utilized US images as they are radiation free, cheap, and always available to detect breast masses. However, this is still a challenging task due to intensity inhomogeneity, shape variations, class imbalanced problems, etc. To solve the shortcomings of US, we proposed three encoder-decoder based neural networks for breast US images segmentation. First, a modified U-Net architecture equipped with pre-trained inception residual blocks as an encoder was presented along with a weighted loss function to handle the class imbalance challenge. Second, a U-Net architecture based residual blocks with convolution paths was introduced to resolve the problem of the vanishing gradient while downsampling the feature maps. Third, a novel attention based segmentation architecture was proposed comprising channel and spatial details; which can be employed efficiently for any segmentation task. Our contributions have proven their robustness and efficiency in the segmentation of breast US tumors.  
Keywords: Neural Networks, BUS Images, lesion Segmentation, Image Processing 

PhD Dissertation Committee:  

Internal Reader: Dr. Christie Ezeife 
Internal Reader: Dr. Dan Wu        
External Reader: Dr. Esam Abdel-Raheem 
External Examiner: Dr. Faisal Qureshi 
Advisor(s):  Dr. Boubakeur Boufama 
Chair:    Dr. Iris Xu (Dept. of Civil and Environmental Engineering) 

 PhD Dissertation Defense Announcement      Vector Institute in Artificial Intelligence, artificial intelligence approved topic logo


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