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Adel Saleh
Rovira i Virgili University
22Publications
4H-index
43Citations
Publications 23
Newest
Abstract Mammogram inspection in search of breast tumors is a tough assignment that radiologists must carry out frequently. Therefore, image analysis methods are needed for the detection and delineation of breast tumors, which portray crucial morphological information that will support reliable diagnosis. In this paper, we proposed a conditional Generative Adversarial Network (cGAN) devised to segment a breast tumor within a region of interest (ROI) in a mammogram. The generative network learns ...
3 CitationsSource
#1Mohamed Abdel-Nasser (URV: Rovira i Virgili University)H-Index: 5
#2Antonio Moreno Jiménez (URV: Rovira i Virgili University)H-Index: 34
Last.Domenec Puig (URV: Rovira i Virgili University)H-Index: 16
view all 7 authors...
Matching candidate points from multiple mammographic views corresponding to the same patient may lead to an improvement in the accuracy of Computer Aided Diagnosis systems and it can help the radiologists to detect breast cancer in early stages, leading to a reduction of the percentage of mortality. In this paper, we propose a matching approach in order to detect correspondences between some candidate points from multiple mammographic views. Initially, a Scale Invariant Feature Transform detecto...
Source
Jan 1, 2019 in VISIGRAPP (International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications)
#1Adel Saleh (URV: Rovira i Virgili University)H-Index: 4
#2Hatem A. Rashwan (URV: Rovira i Virgili University)H-Index: 8
Last.Domenec Puig (URV: Rovira i Virgili University)H-Index: 16
view all 8 authors...
Image semantic segmentation is in the center of interest for computer vision researchers. Indeed, huge number of applications requires efficient segmentation performance, such as activity recognition, navigation, and human body parsing, etc. One of the important applications is gesture recognition that is the ability to understanding human hand gestures by detecting and counting finger parts in a video stream or in still images. Thus, accurate finger parts segmentation yields more accurate gestu...
Source
#2Adel SalehH-Index: 4
Last.Domenec PuigH-Index: 2
view all 3 authors...
Sep 16, 2018 in MICCAI (Medical Image Computing and Computer-Assisted Intervention)
#1Vivek SinghH-Index: 28
#2Santiago RomaniH-Index: 3
Last.Domenec PuigH-Index: 16
view all 12 authors...
This paper proposes a novel approach based on conditional Generative Adversarial Networks (cGAN) for breast mass segmentation in mammography. We hypothesized that the cGAN structure is well-suited to accurately outline the mass area, especially when the training data is limited. The generative network learns intrinsic features of tumors while the adversarial network enforces segmentations to be similar to the ground truth. Experiments performed on dozens of malignant tumors extracted from the pu...
4 CitationsSource
This paper proposed a retinal image segmentation method based on conditional Generative Adversarial Network (cGAN) to segment optic disc. The proposed model consists of two successive networks: generator and discriminator. The generator learns to map information from the observing input (i.e., retinal fundus color image), to the output (i.e., binary mask). Then, the discriminator learns as a loss function to train this mapping by comparing the ground-truth and the predicted output with observing...
2 Citations
Skin lesion segmentation (SLS) in dermoscopic images is a crucial task for automated diagnosis of melanoma. In this paper, we present a robust deep learning SLS model, so-called SLSDeep, which is represented as an encoder-decoder network. The encoder network is constructed by dilated residual layers, in turn, a pyramid pooling network followed by three convolution layers is used for the decoder. Unlike the traditional methods employing a cross-entropy loss, we investigated a loss function by com...
12 Citations
This paper proposes a novel approach based on conditional Generative Adversarial Networks (cGAN) for breast mass segmentation in mammography. We hypothesized that the cGAN structure is well-suited to accurately outline the mass area, especially when the training data is limited. The generative network learns intrinsic features of tumors while the adversarial network enforces segmentations to be similar to the ground truth. Experiments performed on dozens of malignant tumors extracted from the pu...
2 Citations
#1Adel Saleh (URV: Rovira i Virgili University)H-Index: 4
#2Mohamed Abdel-Nasser (Aswan University)H-Index: 5
Last.Domenec Puig (URV: Rovira i Virgili University)H-Index: 16
view all 8 authors...
This paper proposes a new visual embedding method for image classification. It goes further in the analogy with textual data and allows us to read visual sentences in a certain order as in the case of text. The proposed method considers the spatial relations between visual words. It uses a very popular text analysis method called ‘word2vec’. In this method, we learn visual dictionaries based on filters of convolution layers of the convolutional neural network (CNN), which is used to capture the ...
Source
#1Vivek SinghH-Index: 28
#2Hatem A. RashwanH-Index: 8
Last.Domenec PuigH-Index: 16
view all 11 authors...
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