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Cascaded deep convolutional encoder-decoder neural networks for efficient liver tumor segmentation
(Churchıll Lıvıngstone, 2020)
Liver and hepatic tumor segmentation remains a challenging problem in Computer Tomography (CT) images analysis due to its shape variation and vague boundary. The general hypothesis says that deep learning methods produce ...
Transfer learning based histopathologic image classification for breast cancer detection
(Sprınger, 2018)
Breast cancer is one of the leading cancer type among women in worldwide. Many breast cancer patients die every year due to the late diagnosis and treatment. Thus, in recent years, early breast cancer detection systems ...
Efficient deep features selections and classification for flower species recognition
(Elsevıer Scı Ltd, 2019)
Image-based automatic flower species classification is an important problem for the biologists who construct digital flower catalogs. A dozen of work about flower species recognition has been proposed so far based on ...
Neutrosophic Hough Transform
(Mdpı Ag, 2017)
Hough transform (HT) is a useful tool for both pattern recognition and image processing communities. In the view of pattern recognition, it can extract unique features for description of various shapes, such as lines, ...
A novel microaneurysms detection approach based on convolutional neural networks with reinforcement sample learning algorithm
(Bıomed Central Ltd, 2017)
Microaneurysms (MAs) are known as early signs of diabetic-retinopathy which are called red lesions in color fundus images. Detection of MAs in fundus images needs highly skilled physicians or eye angiography. Eye angiography ...
A Retinal Vessel Detection Approach Based on Shearlet Transform and Indeterminacy Filtering on Fundus Images
(Mdpı, 2017)
A fundus image is an effective tool for ophthalmologists studying eye diseases. Retinal vessel detection is a significant task in the identification of retinal disease regions. This study presents a retinal vessel detection ...
A novel retinal vessel detection approach based on multiple deep convolution neural networks
(Elsevıer Ireland Ltd, 2018)
Background and objective: Computer aided detection (CAD) offers an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is a crucial step to identify the retinal disease ...
A retinal vessel detection approach using convolution neural network with reinforcement sample learning strategy
(Elsevıer Scı Ltd, 2018)
Computer-aided detection (CAD) provides an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is an important step to identify the retinal disease regions automatically ...
A Novel Approach Based on Image Processing Algorithms for Microaneurysm Candidate Detection
(Ieee, 2017)
Interpretting color fundus images by doctors is enhanced by computer-aided detection (CAD). Microaneurysm (MA) detection in CAD is an important step to identify the retinal diseases automatically. However, MA detection is ...
A Retinal Verssel Detection Approach Using Convolution Neural Network
(Ieee, 2017)
Computer-aided detection (CAD) provides an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is an important step to identify the retinal disease regions automatically ...
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