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Skin lesion segmentation in clinical images using deep learning

The experimental results show that the proposed method for accurate extraction of lesion region can outperform the existing state-of-the-art algorithms in terms of segmentation accuracy.
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Vessel extraction in X-ray angiograms using deep learning

Experimental results on angiography images of a dataset show that the proposed deep learning approach using convolutional neural networks has a superior performance in extraction of vessel regions.
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Melanoma detection by analysis of clinical images using convolutional neural network.

Experimental results show that the proposed method for detection of melanoma lesions is superior in terms of diagnostic accuracy in comparison with the state-of-the-art methods.
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A Unified Framework Integrating Recurrent Fully-Convolutional Networks and Optical Flow for Segmentation of the Left Ventricle in Echocardiography Data

A method that integrates deep recurrent fully-convolutional networks and optical flow estimation to accurately segment the LV in the apical four-chamber (A4C) view and uses optical flow motion estimation between consecutive frames to improve the segmentation accuracy is presented.
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Melanoma detection by analysis of clinical images using convolutional neural network

Experimental results show that the proposed method for detection of melanoma lesions is superior in terms of diagnostic accuracy in comparison with the state-of-the-art methods.
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Segmentation of vessels in angiograms using convolutional neural networks

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Automatic detection of melanoma using broad extraction of features from digital images

Experimental results show that the proposed method for prescreening of pigmented skin lesions for malignancy using general-purpose digital cameras is superior in diagnosis accuracy compared to state-of-the-art methods.
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Automatic biplane left ventricular ejection fraction estimation with mobile point-of-care ultrasound using multi-task learning and adversarial training

A computationally efficient multi-task deep fully convolutional network is proposed for simultaneous LV segmentation and landmark detection in these views, which is integrated into the LVEF estimation pipeline.
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Automatic detection of melanoma using broad extraction of features from digital images.

Experimental results show that the proposed method for prescreening of pigmented skin lesions for malignancy using general-purpose digital cameras is superior in diagnosis accuracy compared to state-of-the-art methods.
View on PubMed (opens in a new tab)

Extraction of skin lesions from non-dermoscopic images for surgical excision of melanoma

A new method based on deep neural networks is proposed for accurate extraction of a lesion region and can outperform other state-of-the-art algorithms exist in the literature.
View on Springer (opens in a new tab)
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