Francesca Ng
Mount Vernon Hospital
Survival analysisSkewnessData miningInternal medicineRadiologyPathologyOncologyKurtosisStage (cooking)Medical physicsWilcoxon signed-rank testStandard deviationSurvival rateContrast (vision)Texture (geology)NeuroradiologyClinical PracticePrimary tumorImaging ToolTumor StagingPrognostic factorTherapy responseIn patientTumor heterogeneityEnhanced ctComputer scienceProportional hazards modelColorectal cancerImage textureMedicineBiomarker (medicine)
Publications 4
#1Francesca Ng (Mount Vernon Hospital)H-Index: 3
#2Robert Kozarski (University of Hertfordshire)H-Index: 12
Last. Vicky Goh ('KCL': King's College London)H-Index: 59
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OBJECTIVE: To determine if there is a difference between contrast enhanced CT texture features from the largest cross-sectional area versus the whole tumor, and its effect on clinical outcome prediction. METHODS: Entropy (E) and uniformity (U) were derived for different filter values (1.0-2.5: fine to coarse textures) for the largest primary tumor cross-sectional area and the whole tumor of the staging contrast enhanced CT in 55 patients with primary colorectal cancer. Parameters were compared u...
220 CitationsSource
#1Francesca Ng (Mount Vernon Hospital)H-Index: 3
#2Balaji GaneshanH-Index: 32
Last. Vicky GohH-Index: 59
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Fine-texture features (lower entropy, kurtosis, and standard deviation; higher uniformity and skewness) were associated with a poorer 5-year overall survival rate in patients with colorectal cancer.
294 CitationsSource
#1Francesca NgH-Index: 3
#2Robert KozarskiH-Index: 12
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#1Fergus Davnall ('KCL': King's College London)H-Index: 3
#2Connie Yip (Guy's and St Thomas' NHS Foundation Trust)H-Index: 11
Last. Vicky Goh ('KCL': King's College London)H-Index: 59
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Background Tumor spatial heterogeneity is an important prognostic factor, which may be reflected in medical images
525 CitationsSource