Deep Learning Model to Assess Cancer Risk on the Basis of a Breast MR Image Alone

Portnoi Tally; Yala Adam; Schuster Tal; Barzilay Regina; Dontchos Brian; Lamb Leslie; Lehman Constance

首页> 外文期刊>AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences >Deep Learning Model to Assess Cancer Risk on the Basis of a Breast MR Image Alone

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Deep Learning Model to Assess Cancer Risk on the Basis of a Breast MR Image Alone

机译：深入学习模式，以乳房MR图像仅评估癌症风险

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OBJECTIVE The purpose of this study is to develop an image-based deep learning (DL) model to predict the 5-year risk of breast cancer on the basis of a single breast MR image from a screening examination.

机译：目的本研究的目的是开发一种基于图像的深度学习（DL）模型，以预测从筛选检查的单一乳腺MR图像的基础上预测乳腺癌的5年风险。

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《AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences》 |2019年第1期|共7页
作者
Portnoi Tally; Yala Adam; Schuster Tal; Barzilay Regina; Dontchos Brian; Lamb Leslie; Lehman Constance;
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作者单位

MIT Dept Elect Engn &

Comp Sci Cambridge MA 02139 USA;

MIT Dept Elect Engn &

Comp Sci Cambridge MA 02139 USA;

MIT Dept Elect Engn &

Comp Sci Cambridge MA 02139 USA;

MIT Dept Elect Engn &

Comp Sci Cambridge MA 02139 USA;

Harvard Med Sch Dept Radiol Boston MA 02115 USA;

Harvard Med Sch Dept Radiol Boston MA 02115 USA;

Harvard Med Sch Dept Radiol Boston MA 02115 USA;

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原文格式 PDF
正文语种 eng
中图分类放射医学;
关键词
artificial intelligence; breast imaging; deep learning; risk assessment;

机译：人工智能;乳房成像;深入学习;风险评估;

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1. Deep Learning Model to Assess Cancer Risk on the Basis of a Breast MR Image Alone [J] . Portnoi Tally, Yala Adam, Schuster Tal, AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences . 2019,第1期

机译：深入学习模式，以乳房MR图像仅评估癌症风险
2. Harnessing the Power of Deep Learning to Assess Breast Cancer Risk [J] . Bahl Manisha Radiology . 2020,第2期

机译：利用深度学习的力量评估乳腺癌风险
3. DeepBatch: A hybrid deep learning model for interpretable diagnosis of breast cancer in whole-slide images [J] . Zeiser Felipe Andre, da Costa Cristiano Andre, Ramos Gabriel de Oliveira, Expert systems with applications . 2021,第Deca期

机译：深度：一种混合深层学习模型，可解释诊断全幻灯癌中的乳腺癌
4. Deep learning of sub-regional breast parenchyma in mammograms for localized breast cancer risk prediction [C] . Giacomo Nebbia, Aly Mohamed SPIE Conference on Computer-Aided Diagnosis . 2019

机译：乳房X XMIMPORMS局部乳腺癌风险预测中的亚域乳房实质的深度学习
5. Deep Learning Method vs. Hand-Crafted Features for Lung Cancer Diagnosis and Breast Cancer Risk Analysis. [D] . Sun, Wenqing. 2017

机译：肺癌诊断和乳腺癌风险分析的深度学习方法与手工制作功能。
6. Assessing Cancer Risk from Mammograms: Deep Learning Is Superior to Conventional Risk Models [O] . Arkadiusz Sitek, Jeremy M. Wolfe -1

机译：从乳房X线照片评估癌症风险：深度学习优于常规风险模型
7. HIT Poster session 1P154Preclinical diastolic dysfunction is related to impaired endothelial function in patients with chronic kidney diseaseP155Early detection of left atrial and left ventricular abnormalities in hypertensive and obese womenP156Right ventricle preserved systolic function irrespective of right ventricular hypertrophy and disease severity in anderson fabry diseaseP157Left atrial volume and function in patients undergoing percutaneous mitral valve repairP158Impact of left ventricular dysfunction on outcomes of patients undergoing direct TAVI with a self-expanding bioprosthesisP159Anatomic Doppler spectrum – retrospective spectral tissue Doppler from ultra high frame rate tissue Doppler imaging for evaluation of tissue deformationP160Phasic dynamics of ischaemic mitral regurgitation after primary coronary intervention in acute myocardial infarction: serial echocardiographic assessment from emergency room to long-term follow-upP161Reproducibility of 3DE RV volumes - novel insights at a regional levelP162Pulmonary vascular capacitance as assessed by echocardiography in pulmonary arterial hypertensionP163Three-dimensional endocardial area strain: a novel parameter for quantitative assessment of global left ventricular systolic functionP164Role of exercise hemodynamics assessed by echocardiography on symptom reduction after MitraClipP165Early identification of ventricular dysfunction in patients with juvenile systemic sclerosisP166Heart failure with and without preserved ejection fraction - the role of biomarkers in the aspect of global longitudinal strainP167Complex systolic deformation of aortic root: insights from two dimensional speckle tracking imageP168Volumetric and deformational imaging usind 2d strain and 3d echocardiography in patients with pulmonary hypertensionP169Influence of pressure load and right ventricular morphology and function on tricuspid regurgitation in pulmonary arterial hypertensionP170Left ventricular myocardial diastolic deformation analysis by 2D speckle tracking echocardiography and relationship with conventional diastolic parameters in chronic aortic regurgitationP171Extracellular volume, and not native T1 time, distinguishes diffuse fibrosis in dilated or hypertrophic cardiomyopathy at 3TP172Left atrial strain is significantly reduced in arterial hypertensionP173Symptomatic severe secondary mitral regurgitation: LV enddiastolic diameter (LVEDD) as preferable parameter for risk stratificationP174Left ventricular mechanics in isolated left bundle branch block at rest and when exercising: exploration of the concept of conductive cardiomyopathyP175Assessment of myocardial scar by 2D contrast echocardiographyP176Chronic pericarditis - expression of a rare disease: Erdheim Chester diseaseP177Aortic arch mechanics with two-dimensional speckle tracking echocardiography to estimate the left ventricular remodelling in hypertensive patientsP178Strain analysis by tissue doppler imaging: comparison of conventional manual measurement with a semi-automated approachP179Distribution of extravascular lung water in heart failure patients assessed by lung ultrasoudP180Surrogate markers for obstructive coronary artery diseaseP181LA deformation and LV longitudinal strain by two-dimensional speckle tracking echocardiography as predictors of postoperative AF development after aortic valve replacement in ASP182Left ventricular diastolic dysfunction in type 2 diabetic patients with non alcoholic fatty liver diseaseP183Myocardial strain by speckle-tracking and evaluation of 3D ejection fraction in drug-induced cardiotoxicity's approach in breast cancer [O] . AB Gevaert, A Borizanova, F Graziani, 2015

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8. Chemical and Radiation Leukemogenesis in Humans and Rodents and the Value ofRodent Models for Assessing Risks of Lymphohematopoietic Cancers [R] . Eastmond, D. A. 1997

机译：人和啮齿动物的化学和辐射白血病发生及评估淋巴造血细胞癌风险的啮齿动物模型的价值

Deep Learning Model to Assess Cancer Risk on the Basis of a Breast MR Image Alone

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