has been cited by the following article(s):
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Health Seek: A Deep Learning-Based Intelligent System to Aid Medical Diagnosis
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Journal of Biomedical Science and Engineering,
2022 |
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[2]
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Automatic brain lesion segmentation on standard magnetic resonance images: a scoping review
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2021 |
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[3]
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Detección y segmentación de híperintensidades presentes en la sustancia blanca en imágenes de resonancia magnética axiales del cerebro ponderadas en T2 …
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2016 |
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[4]
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Detección y segmentación de híperintensidades presentes en la sustancia blanca en imágenes de resonancia magnética axiales del cerebro ponderadas en T2-FLAIR
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2016 |
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[5]
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Automated detection of white matter and cortical lesions in early stages of multiple sclerosis
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Journal of Magnetic Resonance Imaging,
2015 |
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[6]
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Probabilistic Multiple Sclerosis Lesion Classification based on Modelling Regional Intensity Variability and Local Neighbourhood Information
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Biomedical Engineering, IEEE Transactions,
2014 |
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[7]
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Automatic sperms counting using adaptive local threshold and ellipse detection
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Information Technology Systems and Innovation (ICITSI), 2014 International Conference on,
2014 |
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[8]
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Automated evaluation of gamete and embryo quality for assisted reproduction
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2013 |
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[9]
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Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging
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Medical image analysis,
2013 |
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[10]
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Increasing the Contrast of the Brain MR FLAIR Images Using Fuzzy Membership Functions and Structural Similarity Indices in Order to Segment MS Lesions
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PloS one,
2013 |
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[11]
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Fully automatic identification and discrimination of sperm's parts in microscopic images of stained human semen smear
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Journal of Biomedical Science and Engineering,
2012 |
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[12]
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Automatic determination of MS lesion subtypes based on fractal analysis in brain MR images
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Journal of Biomedical Science and Engineering,
2012 |
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[1]
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Automatic brain lesion segmentation on standard magnetic resonance images: a scoping review
BMJ Open,
2021
DOI:10.1136/bmjopen-2020-042660
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[2]
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Automated detection of white matter and cortical lesions in early stages of multiple sclerosis
Journal of Magnetic Resonance Imaging,
2016
DOI:10.1002/jmri.25095
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[3]
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Probabilistic Multiple Sclerosis Lesion Classification Based on Modeling Regional Intensity Variability and Local Neighborhood Information
IEEE Transactions on Biomedical Engineering,
2015
DOI:10.1109/TBME.2014.2385635
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[4]
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Automatic sperms counting using adaptive local threshold and ellipse detection
2014 International Conference on Information Technology Systems and Innovation (ICITSI),
2014
DOI:10.1109/ICITSI.2014.7048238
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[5]
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Increasing the Contrast of the Brain MR FLAIR Images Using Fuzzy Membership Functions and Structural Similarity Indices in Order to Segment MS Lesions
PLoS ONE,
2013
DOI:10.1371/journal.pone.0065469
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[6]
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Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging
Medical Image Analysis,
2013
DOI:10.1016/j.media.2012.09.004
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[7]
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Fully automatic identification and discrimination of sperm’s parts in microscopic images of stained human semen smear
Journal of Biomedical Science and Engineering,
2012
DOI:10.4236/jbise.2012.57049
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[8]
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Automatic determination of MS lesion subtypes based on fractal analysis in brain MR images
Journal of Biomedical Science and Engineering,
2012
DOI:10.4236/jbise.2012.54021
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