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公开(公告)号：US10402979B2
公开(公告)日：2019-09-03
申请号：US15593497
申请日：2017-05-12
发明人： Mani Abedini , Rajib Chakravorty , Rahil Garnavi , Munawar Hayat
IPC分类号： G06T7/10 , G06T7/13 , G06K9/46 , G06K9/52 , G06K9/62 , G06T7/00 , G06K9/68 , G06T7/143 , G06T7/90 , G06T7/11
摘要： A robust segmentation technique based on multi-layer classification technique to identify the lesion boundary is described. The inventors have discovered a technique based on training several classifiers such that to classify each pixel as lesion versus normal Each classifier is trained on a specific range of image resolutions. Then, for a new test image, the trained classifiers are applied on the image. Then by fusing the prediction results in pixel level a probability map is generated. In the next step, a thresholding method is applied to convert the probability map to a binary mask, which determines a mole border.
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公开(公告)号：US20170287134A1
公开(公告)日：2017-10-05
申请号：US15086988
申请日：2016-03-31
发明人： MANI ABEDINI , Rajib Chakravorty , Rahil Garnavi , Munawar Hayat
CPC分类号： G06T7/11 , G06K9/00147 , G06K9/4628 , G06K9/4638 , G06K9/622 , G06K2209/05 , G06T7/0012 , G06T7/12 , G06T7/136 , G06T7/149 , G06T7/187 , G06T2207/10056 , G06T2207/20081 , G06T2207/20084 , G06T2207/30088
摘要： A method for annotation of skin images includes receiving a plurality of dermatoscopic images. Each of the dermatoscopic includes a region of lesion skin and a region of normal skin. A first convolutional neural network is trained according to an interior of the region of lesion skin using each of the plurality of dermatoscopic images. A second convolutional neural network is trained according to a boundary between the region of lesion skin and the region of normal skin. An additional dermatoscopic image is acquired. The first and second convolutional neural networks are used to identify a region of lesion skin within the acquired additional dermatoscopic image.
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公开(公告)号：US09886758B2
公开(公告)日：2018-02-06
申请号：US15086988
申请日：2016-03-31
发明人： Mani Abedini , Rajib Chakravorty , Rahil Garnavi , Munawar Hayat
CPC分类号： G06T7/11 , G06K9/00147 , G06K9/4628 , G06K9/4638 , G06K9/622 , G06K2209/05 , G06T7/0012 , G06T7/12 , G06T7/136 , G06T7/149 , G06T7/187 , G06T2207/10056 , G06T2207/20081 , G06T2207/20084 , G06T2207/30088
摘要： A method for annotation of skin images includes receiving a plurality of dermatoscopic images. Each of the dermatoscopic includes a region of lesion skin and a region of normal skin. A first convolutional neural network is trained according to an interior of the region of lesion skin using each of the plurality of dermatoscopic images. A second convolutional neural network is trained according to a boundary between the region of lesion skin and the region of normal skin. An additional dermatoscopic image is acquired. The first and second convolutional neural networks are used to identify a region of lesion skin within the acquired additional dermatoscopic image.
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公开(公告)号：US09684967B2
公开(公告)日：2017-06-20
申请号：US14921579
申请日：2015-10-23
发明人： Mani Abedini , Rajib Chakravorty , Rahil Garnavi , Munawar Hayat
CPC分类号： G06T7/13 , G06K9/4604 , G06K9/52 , G06K9/6256 , G06K9/6262 , G06K9/6267 , G06K9/6857 , G06T7/0012 , G06T7/10 , G06T7/11 , G06T7/143 , G06T7/90 , G06T2207/20016 , G06T2207/20021 , G06T2207/20076 , G06T2207/20081 , G06T2207/20112 , G06T2207/30088 , G06T2207/30096
摘要： A robust segmentation technique based on multi-layer classification technique to identify the lesion boundary is described. The inventors have discovered a technique based on training several classifiers such that to classify each pixel as lesion versus normal Each classifier is trained on a specific range of image resolutions. Then, for a new test image, the trained classifiers are applied on the image. Then by fusing the prediction results in pixel level a probability map is generated. In the next step, a thresholding method is applied to convert the probability map to a binary mask, which determines a mole border.
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