AIMC Topic: Tomography, X-Ray Computed

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A natural language processing pipeline for pairing measurements uniquely across free-text CT reports.

Journal of biomedical informatics
OBJECTIVE: To standardize and objectivize treatment response assessment in oncology, guidelines have been proposed that are driven by radiological measurements, which are typically communicated in free-text reports defying automated processing. We st...

Robotic-assisted thermal ablation of liver tumours.

European radiology
OBJECTIVE: This study aimed to assess the technical success, radiation dose, safety and performance level of liver thermal ablation using a computed tomography (CT)-guided robotic positioning system.

Machine learning-based augmented reality for improved surgical scene understanding.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In orthopedic and trauma surgery, AR technology can support surgeons in the challenging task of understanding the spatial relationships between the anatomy, the implants and their tools. In this context, we propose a novel augmented visualization of ...

Photon-Counting Detector CT of the Brain Reduces Variability of Hounsfield Units and Has a Mean Offset Compared with Energy-Integrating Detector CT.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Distinguishing GM from WM is essential for CT of the brain. The recently established photon-counting detector (PCD)-CT technology uses a novel detection technique that might allow more precise measurement of tissue attenuation...

Characterising research trends in bronchiectasis through AI-powered analytics.

The European respiratory journal
BACKGROUND: Interest in bronchiectasis is increasing and no prior study has used artificial intelligence (AI) to interrogate its rich, multidimensional literature to characterise research trends, themes and knowledge gaps.

Non-invasive multi-phase CT artificial intelligence for predicting pre-treatment enlarged lymph node status in colorectal cancer: a prospective validation study.

European radiology
OBJECTIVES: Benign lymph node enlargement can mislead surgeons into overstaging colorectal cancer (CRC), causing unnecessarily extended lymphadenectomy. This study aimed to develop and validate a machine learning (ML) classifier utilizing multi-phase...

The performance of artificial intelligence in image-based prediction of hematoma enlargement: a systematic review and meta-analysis.

Annals of medicine
BACKGROUND: Accurately predicting hematoma enlargement (HE) is crucial for improving the prognosis of patients with cerebral haemorrhage. Artificial intelligence (AI) is a potentially reliable assistant for medical image recognition. This study syste...

Evaluation of artificial-intelligence-based liver segmentation and its application for longitudinal liver volume measurement.

Abdominal radiology (New York)
BACKGROUND: Accurate liver-volume measurements from CT scans are essential for treatment planning, particularly in liver resection cases, to avoid postoperative liver failure. However, manual segmentation is time-consuming and prone to variability. A...

Relationship between spleen volume and diameter for assessment of response to treatment on CT in patients with hematologic malignancies enrolled in clinical trials.

Abdominal radiology (New York)
PURPOSE: Investigate spleen diameter (d) and volume (v) relationship in patients with hematologic malignancies (HM) by determining volumetric thresholds that best correlate to established diameter thresholds for assessing response to treatment. Explo...