AIMC Topic: Retrospective Studies

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Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT.

Radiology
Background Adrenal masses are common, but radiology reporting and recommendations for management can be variable. Purpose To create a machine learning algorithm to segment adrenal glands on contrast-enhanced CT images and classify glands as normal or...

Robot-Assisted Versus Laparoscopic Approach for Splenectomy in Children: Systematic Review and Meta-Analysis.

Journal of laparoendoscopic & advanced surgical techniques. Part A
To compare the outcomes of pediatric splenectomies for hematologic diseases performed by robot-assisted laparoscopic surgery (RALS) and laparoscopic approach. Web of Science, Scopus, and PubMed databases were systematically searched for publication...

Validation of deep learning-based computer-aided detection software use for interpretation of pulmonary abnormalities on chest radiographs and examination of factors that influence readers' performance and final diagnosis.

Japanese journal of radiology
PURPOSE: To evaluate the performance of a deep learning-based computer-aided detection (CAD) software for detecting pulmonary nodules, masses, and consolidation on chest radiographs (CRs) and to examine the effect of readers' experience and data char...

Choreography Controlled (ChoCo) brain MRI artifact generation for labeled motion-corrupted datasets.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
MRI is a non-invasive medical imaging modality that is sensitive to patient motion, which constitutes a major limitation in most clinical applications. Solutions may arise from the reduction of acquisition times or from motion-correction techniques, ...

Development and evaluation of deep-learning measurement of leg length discrepancy: bilateral iliac crest height difference measurement.

Pediatric radiology
BACKGROUND: Leg length discrepancy (LLD) is a common problem that can cause long-term musculoskeletal problems. However, measuring LLD on radiography is time-consuming and labor intensive, despite being a simple task.

Deep learning in automatic detection of dysphonia: Comparing acoustic features and developing a generalizable framework.

International journal of language & communication disorders
BACKGROUND: Auditory-perceptual assessment of voice is a subjective procedure. Artificial intelligence with deep learning (DL) may improve the consistency and accessibility of this task. It is unclear how a DL model performs on different acoustic fea...

Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in dual-energy CT of the abdomen: a phantom and clinical study.

European radiology
OBJECTIVES: To investigate the effect of deep learning image reconstruction (DLIR) on the accuracy of iodine quantification and image quality of dual-energy CT (DECT) compared to that of other reconstruction algorithms in a phantom experiment and an ...

Leveraging Artificial Intelligence to Enhance Peer Review: Missed Liver Lesions on Computed Tomographic Pulmonary Angiography.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to use artificial intelligence (AI) to facilitate peer review for detection of missed suspicious liver lesions (SLLs) on CT pulmonary angiographic (CTPA) examinations.

Biparametric prostate MRI: impact of a deep learning-based software and of quantitative ADC values on the inter-reader agreement of experienced and inexperienced readers.

La Radiologia medica
OBJECTIVE: To investigate the impact of an artificial intelligence (AI) software and quantitative ADC (qADC) on the inter-reader agreement, diagnostic performance, and reporting times of prostate biparametric MRI (bpMRI) for experienced and inexperie...

[Robot-assisted Thoracic Surgery: Learning Curve and Cost Analysis in a German High-Volume Centre].

Zentralblatt fur Chirurgie
Robot-assisted thoracic surgery (RATS) is a rapidly evolving surgical technique in Europe. The aim of the study was to analyse the learning curve and safety during the establishment of a RATS-program at a high-volume thoracic surgery centre and to qu...