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

@article{Jafari2017ExtractionOS,
  title={Extraction of skin lesions from non-dermoscopic images for surgical excision of melanoma},
  author={M. Jafari and Ebrahim Nasr-Esfahani and Nader Karimi and S. Mohamad R. Soroushmehr and Shadrokh Samavi and Kayvan Najarian},
  journal={International Journal of Computer Assisted Radiology and Surgery},
  year={2017},
  volume={12},
  pages={1021-1030}
}
PurposeComputerized prescreening of suspicious moles and lesions for malignancy is of great importance for assessing the need and the priority of the removal surgery. Detection can be done by images captured by standard cameras, which are more preferable due to low cost and availability. One important step in computerized evaluation is accurate detection of lesion’s region, i.e., segmentation of an image into two regions as lesion and normal skin.MethodsIn this paper, a new method based on deep… 
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U-Net Based Segmentation and Multiple Feature Extraction of Dermascopic Images for Efficient Diagnosis of Melanoma

  • D. RamaniS. Ranjani
  • Medicine, Computer Science
    Computer Aided Intervention and Diagnostics in Clinical and Medical Images
  • 2019
A U-Net based segmentation and multiple feature extraction of the dermascopic images for the efficient diagnosis of skin cancer is presented and yields better performance than the existing segmentations and feature extraction techniques.

Medical image learning from a few/few training samples: Melanoma segmentation study

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Melanoma diagnosis using deep learning techniques on dermatoscopic images

The results achieved with the proposed model suggest a significant improvement over the results obtained in the state of the art as far as performance of skin lesion classifiers (malignant/benign) is concerned.

Skin lesion segmentation using object scale-oriented fully convolutional neural networks

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MelaNet: an effective deep learning framework for melanoma detection using dermoscopic images

An improved deep learning-based solution with a convolutional neural network is proposed that can be adopted for assisting dermatologists with melanoma diagnosis and the obtained results demonstrate its effectiveness when compared to the state-of-the-art methods.

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...

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