International journal of computer assisted radiology and surgery
May 23, 2022
PURPOSE: Recently, a large number of patients with acute ischemic stroke benefited from the use of thrombectomy, a minimally invasive intervention technique for mechanically removing thrombi from the cerebrovasculature. During thrombectomy, 2D digita...
BACKGROUND: The development of an advanced robotic platform in 2014 led to increased adoption of minimally invasive (MI) approaches in thoracic surgery. Due to dataset reporting lag, a comprehensive assessment of trends in thoracic approaches has not...
OBJECTIVES: To propose deep-learning (DL)-based predictive model for pathological complete response rate for resectable locally advanced esophageal squamous cell carcinoma (SCC) after neoadjuvant chemoradiotherapy (NCRT) with endoscopic images.
OBJECTIVE: To train and validate a code-free deep learning system (CFDLS) on classifying high-resolution digital retroillumination images of posterior capsule opacification (PCO) and to discriminate between clinically significant and non-significant ...
PURPOSE: To assess the value of novel deep learning (DL) scores combined with complementary lung imaging reporting and data system 1.1 (cLung-RADS 1.1) in managing the risk stratification of ground-glass nodules (GGNs) and therefore improving the eff...
This study aimed to develop a supervised deep learning (DL) model for grading collateral status from dynamic susceptibility contrast magnetic resonance perfusion (DSC-MRP) images from patients with large vessel occlusion (LVO) acute ischemic stroke (...
OBJECTIVES: To explore the impact of deep learning reconstruction (DLR) on image quality and machine learning-based coronary CT angiography (CTA)-derived fractional flow reserve (CT-FFR) values.
The aim of the study described here was to investigate the value of different machine learning models based on the clinical and radiomic features of 2-D ultrasound images to evaluate post-transplant renal function (pTRF). We included 233 patients who...
The study's aim was to externally validate a new predictive model for the new baseline glomerular filtration rate (NB-GFR) postnephrectomy among Japanese patients. Patients with renal tumors who underwent radical nephrectomy (RN) or robot-assisted ...
Journal of magnetic resonance imaging : JMRI
May 19, 2022
BACKGROUND: Recent studies showed the potential of MRI-based deep learning (DL) for assessing treatment response in rectal cancer, but the role of MRI-based DL in evaluating Kirsten rat sarcoma viral oncogene homologue (KRAS) mutation remains unclear...
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