AIMC Topic: Parathyroid Glands
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A visual deep learning model to predict abnormal versus normal parathyroid glands using intraoperative autofluorescence signals.
Journal of surgical oncology
Apr 13, 2022
BACKGROUND: Previous work demonstrated that abnormal versus normal parathyroid glands (PGs) exhibit different patterns of autofluorescence, with former appearing darker and more heterogenous. Our objective was to develop a visual artificial intellige...
Deep learning-based detection of parathyroid adenoma by Tc-MIBI scintigraphy in patients with primary hyperparathyroidism.
Annals of nuclear medicine
Feb 18, 2022
OBJECTIVE: It is important to detect parathyroid adenomas by parathyroid scintigraphy with 99m-technetium sestamibi (Tc-MIBI) before surgery. This study aimed to develop and validate deep learning (DL)-based models to detect parathyroid adenoma in pa...
Development of an algorithm for intraoperative autofluorescence assessment of parathyroid glands in primary hyperparathyroidism using artificial intelligence.
Surgery
Mar 3, 2021
BACKGROUND: Previous work showed that normal and abnormal parathyroid glands exhibit different patterns of autofluorescence, with the former appearing brighter and more homogenous. However, an objective algorithm based on quantified measurements was ...
Parathyroid hormone in washout fluid seems to be superior to cytology for localization of the lesion in MIBI-negative patients with primary hyperparathyroidism.
Turkish journal of medical sciences
Dec 19, 2017
Background/aim: Primary hyperparathyroidism (PHPT) is characterized by increased calcium (Ca) and parathyroid hormone (PTH) levels. Surgical removal of the culprit hyperfunctioning parathyroid gland is the preferred treatment. In this study, we aimed...
Machine learning to identify multigland disease in primary hyperparathyroidism.
The Journal of surgical research
Jun 29, 2017
BACKGROUND: 20%-25% of patients with primary hyperparathyroidism will have multigland disease (MGD). Preoperatative imaging can be inaccurate or unnecessary in MGD. Identification of MGD could direct the need for imaging and inform operative approach...
Parathyroid gland identification and angiography classification using simple machine learning methods.
BJS open
Sep 3, 2024
BACKGROUND: Near-infrared indocyanine green angiography allows experienced surgeons to reliably evaluate parathyroid gland vitality during thyroid and parathyroid operations in order to predict postoperative function. To facilitate equal performance ...
An automatic parathyroid recognition and segmentation model based on deep learning of near-infrared autofluorescence imaging.
Cancer medicine
Feb 1, 2024
INTRODUCTION: Near-infrared autofluorescence imaging (NIFI) can be used to identify parathyroid gland (PG) during surgery. The purpose of the study is to establish a new model, help surgeons better identify, and protect PGs.
Fuzzy logic-based moving average filters for reducing noise from Tc-99m-sestamibi parathyroid images.
Nuclear medicine communications
Aug 1, 2021
INTRODUCTION: The objective of the study was to use fuzzy logic-based moving average filters for reducing noise from Tc-99m-sestamibi parathyroid images and to compare its performance with classical moving average filters.
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