Radiology

Combining Deep Learning and Handcrafted Radiomics for Classification of Suspicious Lesions on Contrast-enhanced Mammograms.

Background Handcrafted radiomics and deep learning (DL) models individually achieve good performance...

Artificial Intelligence Applied to Contrast-enhanced Mammography: Exploring Uncharted Territory.

[Segmentation of acute pulmonary embolism in computed tomography pulmonary angiography using the deep learning method].

ABSTRACT: Segmentation of acute pulmonary embolism in computed tomography pulmonary angiography usin...

[Quality of Images Reconstructed by Deep Learning Reconstruction Algorithm for Head and Neck CT Angiography at 100 kVp].

Objective To evaluate the impact of deep learning reconstruction algorithm on the image quality of h...

Evaluating a 3D deep learning pipeline for cerebral vessel and intracranial aneurysm segmentation from computed tomography angiography-digital subtraction angiography image pairs.

OBJECTIVE: Computed tomography angiography (CTA) is the most widely used imaging modality for intrac...

[The application value of deep learning image reconstruction on improving image quality and evaluating the Qanadli embolism index of dual low-dose CT pulmonary angiography].

To compare the image quality and Qanadli embolism index between deep learning image reconstruction ...

Radiomics in colorectal cancer patients.

The main therapeutic options for colorectal cancer are surgical resection and adjuvant chemotherapy ...

Anticipating artificial intelligence in mammography screening: views of Swedish breast radiologists.

OBJECTIVES: Artificial intelligence (AI) is increasingly tested and integrated into breast cancer sc...

Artificial Intelligence in Clinical Oncology: From Data to Digital Pathology and Treatment.

Recently, a wide spectrum of artificial intelligence (AI)-based applications in the broader categori...

[A Case of Refractory Lymphatic Leakage after Robot-Assisted Radical Cystectomy].

A 78-year-old male visited the referring hospital because of asymptomatic gross hematuria. The patie...

[CT and MRI fusion based on generative adversarial network and convolutional neural networks under image enhancement].

Aiming at the problems of missing important features, inconspicuous details and unclear textures in ...

Deep Learning for Diagnosing and Segmenting Choroidal Neovascularization in OCT Angiography in a Large Real-World Data Set.

PURPOSE: To diagnose and segment choroidal neovascularization (CNV) in a real-world multicenter clin...

Artificial intelligence for detection of intracranial haemorrhage on head computed tomography scans: diagnostic accuracy in Hong Kong.

INTRODUCTION: The use of artificial intelligence (AI) to identify acute intracranial haemorrhage (IC...

RESEARCH PROGRESS OF DEEP LEARNING IN LOW-DOSE CT IMAGE DENOISING.

Low-dose computed tomography (CT) will increase noise and artefacts while reducing the radiation dos...

Clinical impact of artificial intelligence-based solutions on imaging of the pancreas and liver.

Artificial intelligence (AI) has experienced substantial progress over the last ten years in many fi...

Ontologies in the New Computational Age of Radiology: RadLex for Semantics and Interoperability in Imaging Workflows.

From basic research to the bedside, precise terminology is key to advancing medicine and ensuring op...

[Mullerian Cyst in the Posterior Mediastinum Resected by Robot-assisted Thoracic Surgery:Report of a Case].

Mullerian cyst in the posterior mediastinum is a rare disorder. We report on the case of a woman in ...

Outcomes of Robot-Assisted Laparoscopic Pyeloplasty Based on Degree of Obstruction on Preoperative Tc-99 MAG-3 Renal Scintigraphy.

Management of symptomatic ureteropelvic junction (UPJ) obstruction with hydronephrosis and discorda...

Image Quality Assessment of Deep Learning Image Reconstruction in Torso Computed Tomography Using Tube Current Modulation.

Novel deep learning image reconstruction (DLIR) reportedly changes the image quality characteristics...

An Arbitrary Scale Super-Resolution Approach for 3D MR Images via Implicit Neural Representation.

High Resolution (HR) medical images provide rich anatomical structure details to facilitate early an...

Improving artificial intelligence pipeline for liver malignancy diagnosis using ultrasound images and video frames.

Recent developments of deep learning methods have demonstrated their feasibility in liver malignancy...