Nesrine Bnouni

Nesrine Bnouni
Ecole Nationale d'Ingénieurs de Souss | Eniso

PhD

About

10
Publications
1,197
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32
Citations

Publications

Publications (10)
Chapter
Generative Adversarial Networks (GANs) have increasingly broken records in solving challenging medical image analyses problems such as medical image de-noising, segmentation, detection, classification or reconstruction. However, to the best of our knowledge, they have not been used for female pelvic multi-organ segmentation. Accurate segmentation o...
Article
Pelvic Lymph Nodes (PLNs) segmentation and classification are fundamental tools in the medical image analysis of pelvic gynecological cancer such as endometrial and cervical cancer. Often used by the radiologist, PLN classification requires detailed knowledge of the morphological features of PLNs, derived from size, shape, contour and heterogeneous...
Article
Full-text available
Dictionary Learning (DL) has gained large popularity in solving different computer vision and medical image problems. However, to the best of our knowledge, it has not been used for cervical tumor staging. More importantly, there have been very limited works on how to aggregate different interactions across data views using dictionary learning. As...
Chapter
Deep-learning based labeling methods have gained unprecedented popularity in different computer vision and medical image segmentation tasks. However, to the best of our knowledge, these have not been used for cervical tumor segmentation. More importantly, while the majority of innovative deep-learning works using convolutional neural networks (CNNs...
Conference Paper
Full-text available
Deep-learning based labeling methods have gained unprecedented popularity in different computer vision and medical image segmentation tasks. However, to the best of our knowledge, these have not been used for cervical tumor segmentation. More importantly, while the majority of innovative deep- learning works using convolutional neural networks (CNN...
Conference Paper
Deep-learning based labeling methods have gained unprecedented popularity in different computer vision and medical image segmentation tasks. However, to the best of our knowledge, these have not been used for cervical tumor segmentation. More importantly, while the majority of innovative deep-learning works using convolutional neural networks (CNNs...
Conference Paper
Full-text available
Recently, there has been an increasing interest in using 3D facial images as biometric modality. To that end, a proper representation of the 3D facial shape that would allow effective face matching is a major requirement. In this paper, we propose a novel 3D facial representation, dubbed, the face-tree. We describe the extraction process of this re...

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