AIMC Topic: Magnetic Resonance Imaging
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PatchResNet: Multiple Patch Division-Based Deep Feature Fusion Framework for Brain Tumor Classification Using MRI Images.
Journal of digital imaging
Feb 16, 2023
Modern computer vision algorithms are based on convolutional neural networks (CNNs), and both end-to-end learning and transfer learning modes have been used with CNN for image classification. Thus, automated brain tumor classification models have bee...
Deep learning for the ovarian lesion localization and discrimination between borderline and malignant ovarian tumors based on routine MR imaging.
Scientific reports
Feb 16, 2023
To establish a deep learning (DL) model in differentiating borderline ovarian tumor (BOT) from epithelial ovarian cancer (EOC) on conventional MR imaging. We retrospectively enrolled 201 patients of 102 pathologically proven BOTs and 99 EOCs at OB/GY...
Deep learning nomogram based on Gd-EOB-DTPA MRI for predicting early recurrence in hepatocellular carcinoma after hepatectomy.
European radiology
Feb 14, 2023
OBJECTIVES: The accurate prediction of post-hepatectomy early recurrence in patients with hepatocellular carcinoma (HCC) is crucial for decision-making regarding postoperative adjuvant treatment and monitoring. We aimed to explore the feasibility of ...
Deep learning-based prediction of intra-cardiac blood flow in long-axis cine magnetic resonance imaging.
The international journal of cardiovascular imaging
Feb 10, 2023
PURPOSE: We aimed to design and evaluate a deep learning-based method to automatically predict the time-varying in-plane blood flow velocity within the cardiac cavities in long-axis cine MRI, validated against 4D flow.
Deep Learning Algorithm for Identifying Cervical Cord Compression Due to Degenerative Canal Stenosis on Radiography.
Spine
Feb 10, 2023
STUDY DESIGN: Cross-sectional study.
Developing a machine learning algorithm to predict probability of retear and functional outcomes in patients undergoing rotator cuff repair surgery: protocol for a retrospective, multicentre study.
BMJ open
Feb 10, 2023
INTRODUCTION: The effectiveness of rotator cuff tear repair surgery is influenced by multiple patient-related, pathology-centred and technical factors, which is thought to contribute to the reported retear rates between 17% and 94%. Adequate patient ...
Deep learning applications in osteoarthritis imaging.
Skeletal radiology
Feb 9, 2023
Deep learning (DL) is one of the most exciting new areas in medical imaging. This article will provide a review of current applications of DL in osteoarthritis (OA) imaging, including methods used for cartilage lesion detection, OA diagnosis, cartila...
Synthetic cranial MRI from 3D optical surface scans using deep learning for radiation therapy treatment planning.
Physical and engineering sciences in medicine
Feb 8, 2023
BACKGROUND: Optical scanning technologies are increasingly being utilised to supplement treatment workflows in radiation oncology, such as surface-guided radiotherapy or 3D printing custom bolus. One limitation of optical scanning devices is the abse...
Assessment of artificial intelligence (AI) reporting methodology in glioma MRI studies using the Checklist for AI in Medical Imaging (CLAIM).
Neuroradiology
Feb 7, 2023
PURPOSE: The Checklist for Artificial Intelligence in Medical Imaging (CLAIM) is a recently released guideline designed for the optimal reporting methodology of artificial intelligence (AI) studies. Gliomas are the most common form of primary maligna...
The Evidence for Using Artificial Intelligence to Enhance Prostate Cancer MR Imaging.
Current oncology reports
Feb 7, 2023
PURPOSE OF REVIEW: The purpose of this review is to summarize the current status of artificial intelligence applied to prostate cancer MR imaging.
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