Detection of deep myometrial invasion in endometrial cancer MR imaging based on multi-feature fusion and probabilistic support vector machine ensemble

Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

(2021) Hyuna Sung et al.   CA-A CANCER JOURNAL FOR CLINICIANS

The apparent diffusion coefficient (ADC) on 3-T MRI differentiates myometrial invasion depth and histological grade in patients with endometrial cancer

(2020) Juan Armando Reyes-Pérez et al.   ACTA RADIOLOGICA

Quantitative assessment of diffusion kurtosis imaging depicting deep myometrial invasion: a comparative analysis with diffusion-weighted imaging

(2020) Jia-Cheng Song et al.   Diagnostic and Interventional Radiology

Deep learning for the determination of myometrial invasion depth and automatic lesion identification in endometrial cancer MR imaging: a preliminary study in a single institution

(2020) Xiaojun Chen et al.   EUROPEAN RADIOLOGY

Kidney segmentation from computed tomography images using deep neural network

(2020) Luana Batista da Cruz et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Using Deep Learning with Convolutional Neural Network Approach to Identify the Invasion Depth of Endometrial Cancer in Myometrium Using MR Images: A Pilot Study

(2020) Hsiang-Chun Dong et al.   International Journal of Environmental Research and Public Health

Automated Decision Support System for Lung Cancer Detection and Classification via Enhanced RFCN With Multilayer Fusion RPN

(2020) Anum Masood et al.   IEEE Transactions on Industrial Informatics

Hyperparameters and tuning strategies for random forest

(2019) Philipp Probst et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

DTI histogram parameters correlate with the extent of myoinvasion and tumor type in endometrial carcinoma: a preliminary analysis

(2019) Adarsh Ghosh et al.   ACTA RADIOLOGICA

MR volumetry in predicting the aggressiveness of endometrioid adenocarcinoma: correlation with final pathological results

(2019) Shulei Cai et al.   ACTA RADIOLOGICA

Automatic segmentation of the uterus on MRI using a convolutional neural network

(2019) Yasuhisa Kurata et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Deep Learning-Based Segmentation of Nodules in Thyroid Ultrasound: Improving Performance by Utilizing Markers Present in the Images

(2019) Mateusz Buda et al.   ULTRASOUND IN MEDICINE AND BIOLOGY

Preoperative prediction of deep myometrial invasion and tumor grade for stage I endometrioid adenocarcinoma: a simple method of measurement on DWI

(2018) Bin Yan et al.   EUROPEAN RADIOLOGY

Preoperative tumor texture analysis on MRI predicts high-risk disease and reduced survival in endometrial cancer

(2018) Sigmund Ytre-Hauge et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Cancer of the corpus uteri

(2018) Frédéric Amant et al.   INTERNATIONAL JOURNAL OF GYNECOLOGY & OBSTETRICS

Endometrial Carcinoma: MR Imaging–based Texture Model for Preoperative Risk Stratification—A Preliminary Analysis

(2017) Yoshiko Ueno et al.   RADIOLOGY

Exploiting ensemble learning for automatic cataract detection and grading

(2016) Ji-Jiang Yang et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Assessment of deep myometrial invasion of endometrial cancer on MRI: added value of second-opinion interpretations by radiologists subspecialized in gynaecologic oncology

(2016) Sungmin Woo et al.   EUROPEAN RADIOLOGY

Automated detection and measurement of uterine peristalsis in cine MR images

(2014) Koichi Watanabe et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Standard 1.5-T MRI of endometrial carcinomas: modest agreement between radiologists

(2012) Ingfrid S. Haldorsen et al.   EUROPEAN RADIOLOGY

FIGO Staging System for Endometrial Cancer: Added Benefits of MR Imaging

(2012) Peter Beddy et al.   RADIOGRAPHICS

Magnetic Resonance Imaging of Endometrial Carcinoma

(2009) Silanath Peungjesada et al.   JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY