A novel and fully automated mammographic texture analysis for risk prediction: results from two case-control studies

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Using Convolutional Neural Networks for Enhanced Capture of Breast Parenchymal Complexity Patterns Associated with Breast Cancer Risk.Exploring the prediction performance for breast cancer risk based on volumetric mammographic density at different thresholds.

P2860

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A novel and fully automated mammographic texture analysis for risk prediction: results from two case-control studies

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2017 nî lūn-bûn

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2017年論文

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2017年論文

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2017年論文

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2017年论文

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A novel and fully automated ma ...... from two case-control studies

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A novel and fully automated ma ...... from two case-control studies

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A novel and fully automated ma ...... from two case-control studies

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A novel and fully automated ma ...... from two case-control studies

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A novel and fully automated ma ...... from two case-control studies

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A novel and fully automated ma ...... from two case-control studies

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P1476

A novel and fully automated ma ...... from two case-control studies

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Elaine F Harkness

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Jack Cuzick

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Susan Astley

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P2860

Beyond breast density: a review on the advancing role of parenchymal texture analysis in breast cancer risk assessment

Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring

Regularization Paths for Generalized Linear Models via Coordinate Descent

Mammographic texture resemblance generalizes as an independent risk factor for breast cancer

Breast density and parenchymal texture measures as potential risk factors for Estrogen-Receptor positive breast cancer.

Relationships between computer-extracted mammographic texture pattern features and BRCA1/2 mutation status: a cross-sectional study

Analysis of parenchymal texture with digital breast tomosynthesis: comparison with digital mammography and implications for cancer risk assessment.

Parenchymal texture analysis in digital mammography: A fully automated pipeline for breast cancer risk assessment.

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation.

Characterizing mammographic images by using generic texture features

P2888

s13058-017-0906-6

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scholarly article

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10.1186/S13058-017-0906-6

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Gareth Evans

Adam R Brentnall

Chao Wang

P577

2017-10-18T00:00:00Z

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1092273208

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A novel and fully automated mammographic texture analysis for risk prediction: results from two case-control studies

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P2860

P2860

A novel and fully automated mammographic texture analysis for risk prediction: results from two case-control studies

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P1476

P2093

P2860

P2888

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P356

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P6179

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P1433

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P2860

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P50

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P6179

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P932