Improving the distinction between benign and malignant breast lesions: the value of sonographic texture analysis.
about
Robust phase-based texture descriptor for classification of breast ultrasound imagesImprovement in diagnosis of breast tumour using ultrasound elastography and echography: A phantom based analysisAnniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.Malignant and benign breast masses on 3D US volumetric images: effect of computer-aided diagnosis on radiologist accuracyDifferentiation of pancreatic cancer and chronic pancreatitis using computer-aided diagnosis of endoscopic ultrasound (EUS) images: a diagnostic testAutomatic detection and classification of breast tumors in ultrasonic images using texture and morphological features.Quantification of heterogeneity as a biomarker in tumor imaging: a systematic reviewParenchymal texture analysis in digital mammography: A fully automated pipeline for breast cancer risk assessment.Breast ultrasound image classification based on multiple-instance learning.Multimodality computer-aided breast cancer diagnosis with FFDM and DCE-MRI.Comparative analysis of texture characteristics of malignant and benign tumors in breast ultrasonograms.Texture features from mammographic images and risk of breast cancerA new endoscopic ultrasonography image processing method to evaluate the prognosis for pancreatic cancer treated with interstitial brachytherapy.Radiomics: a new application from established techniques.Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification.Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.Feature selection and classifier performance in computer-aided diagnosis: the effect of finite sample size.Differentiation of intracardiac tumors and thrombi by echocardiographic tissue characterization: comparison of an artificial neural network and human observers.Temporal lobe epilepsy: differential pattern of damage in temporopolar cortex and white matter.Machine learning for medical ultrasound: status, methods, and future opportunities.Assessing the combined performance of texture and morphological parameters in distinguishing breast tumors in ultrasound images.The biological correlates of macroscopic breast tumour structure measured using fractal analysis in patients undergoing neoadjuvant chemotherapy
P2860
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P2860
Improving the distinction between benign and malignant breast lesions: the value of sonographic texture analysis.
description
1993 nî lūn-bûn
@nan
1993年の論文
@ja
1993年学术文章
@wuu
1993年学术文章
@zh
1993年学术文章
@zh-cn
1993年学术文章
@zh-hans
1993年学术文章
@zh-my
1993年学术文章
@zh-sg
1993年學術文章
@yue
1993年學術文章
@zh-hant
name
Improving the distinction betw ...... sonographic texture analysis.
@en
Improving the distinction betw ...... sonographic texture analysis.
@nl
type
label
Improving the distinction betw ...... sonographic texture analysis.
@en
Improving the distinction betw ...... sonographic texture analysis.
@nl
prefLabel
Improving the distinction betw ...... sonographic texture analysis.
@en
Improving the distinction betw ...... sonographic texture analysis.
@nl
P2093
P356
P1433
P1476
Improving the distinction betw ...... sonographic texture analysis.
@en
P2093
P304
P356
10.1006/UIMG.1993.1017
P577
1993-10-01T00:00:00Z