Diagnostic classification of solitary pulmonary nodules using dual time 18F-FDG PET/CT image texture features in granuloma-endemic regions.

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Exploration of PET and MRI radiomic features for decoding breast cancer phenotypes and prognosis

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P2860

Diagnostic classification of solitary pulmonary nodules using dual time 18F-FDG PET/CT image texture features in granuloma-endemic regions.

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2017 nî lūn-bûn

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2017年論文

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2017年论文

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name

Diagnostic classification of s ...... in granuloma-endemic regions.

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Diagnostic classification of s ...... in granuloma-endemic regions.

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Diagnostic classification of s ...... in granuloma-endemic regions.

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P1476

Diagnostic classification of s ...... s in granuloma-endemic regions

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Meijie Chen

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Robert Jeraj

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Song Chen

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Stephanie Harmon

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Xuena Li

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Yaming Li

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P2860

Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach

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Computerized assessment of breast lesion malignancy using DCE-MRI robustness study on two independent clinical datasets from two manufacturers.

A clinical model to estimate the pretest probability of lung cancer in patients with solitary pulmonary nodules.

Texture feature analysis for computer-aided diagnosis on pulmonary nodules.

Evaluation of a cumulative SUV-volume histogram method for parameterizing heterogeneous intratumoural FDG uptake in non-small cell lung cancer PET studies

Voxel-based texture analysis of the brain.

Imaging of solitary pulmonary nodule-a clinical review

P2888

s41598-017-08764-7

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scholarly article

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10.1038/S41598-017-08764-7

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English

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Timothy Perk

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2017-08-24T00:00:00Z

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28839156

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5571049

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Diagnostic classification of solitary pulmonary nodules using dual time 18F-FDG PET/CT image texture features in granuloma-endemic regions.

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P2860

P2860

Diagnostic classification of solitary pulmonary nodules using dual time 18F-FDG PET/CT image texture features in granuloma-endemic regions.

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