AIMC Topic: Adrenal Glands

Clear Filters Showing 1 to 10 of 16 articles

A deep learning algorithm for automated adrenal gland segmentation on non-contrast CT images.

BMC medical imaging
BACKGROUND: The adrenal glands are small retroperitoneal organs, few reference standards exist for adrenal CT measurements in clinical practice. This study aims to develop a deep learning (DL) model for automated adrenal gland segmentation on non-con...

Circulating miRNAs and Machine Learning for Lateralizing Primary Aldosteronism.

Hypertension (Dallas, Tex. : 1979)
BACKGROUND: Distinguishing between unilateral and bilateral primary aldosteronism, a major cause of secondary hypertension, is crucial due to different treatment approaches. While adrenal venous sampling is the gold standard, its invasiveness, limite...

Adrenal Volume Quantitative Visualization Tool by Multiple Parameters and an nnU-Net Deep Learning Automatic Segmentation Model.

Journal of imaging informatics in medicine
Abnormalities in adrenal gland size may be associated with various diseases. Monitoring the volume of adrenal gland can provide a quantitative imaging indicator for such conditions as adrenal hyperplasia, adrenal adenoma, and adrenal cortical adenoca...

Utilization of artificial intelligence in minimally invasive right adrenalectomy: recognition of anatomical landmarks with deep learning.

Acta chirurgica Belgica
BACKGROUND: The primary surgical approach for removing adrenal masses is minimally invasive adrenalectomy. Recognition of anatomical landmarks during surgery is critical for minimizing complications. Artificial intelligence-based tools can be utilize...

Machine Learning Model with Computed Tomography Radiomics and Clinicobiochemical Characteristics Predict the Subtypes of Patients with Primary Aldosteronism.

Academic radiology
RATIONALE AND OBJECTIVES: Adrenal venous sampling (AVS) is the primary method for differentiating between primary aldosterone (PA) subtypes. The aim of study is to develop prediction models for subtyping of patients with PA using computed tomography ...

Fully automatic volume measurement of the adrenal gland on CT using deep learning to classify adrenal hyperplasia.

European radiology
OBJECTIVES: To develop a fully automated deep learning model for adrenal segmentation and to evaluate its performance in classifying adrenal hyperplasia.

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...

Surgical Approaches to the Adrenal Gland.

The Surgical clinics of North America
Adrenalectomy can be performed open, endoscopically or robotically, utilizing a transabdominal or retroperitoneal approach. This chapter describes the relevant anatomy, various approaches and surgical techniques, pre-operative work-up and optimizatio...

Computer-assisted prediction of atherosclerotic intimal thickness based on weight of adrenal gland, interleukin-6 concentration, and neural networks.

The Journal of international medical research
OBJECTIVE: Atherosclerosis (AS) is the main pathological basis of ischemic cardio-cerebrovascular diseases, and the intimal thickness (IT) of large arteries is regarded as a powerful evaluation indicator for AS. We established an effective neural net...