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Objectives: To evaluate the performance of a 3D V-Net-based segmentation model of adrenal lesions in characterizing adrenal glands as normal or abnormal.

Methods: A total of 1086 CT image series with focal adrenal lesions were retrospectively collected, annotated, and used for the training of the adrenal lesion segmentation model. The dice similarity coefficient (DSC) of the test set was used to evaluate the segmentation performance.

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Purpose Of Review: Our purpose was to discuss the advantages and disadvantages of various noninvasive imaging modalities in the evaluation of cardiovascular disease (CVD) in patients with autoimmune rheumatic diseases (ARDs). The detailed knowledge of imaging modalities will facilitate the diagnosis and follow up of CVD in ARDs.

Recent Findings: Autoimmune Rheumatic Diseases (ARDs) are characterized by alterations in immunoregulatory system of the body.

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Background: The standard approach for addressing intra-articular calcaneal fractures involves open reduction with plate and screw fixation, with ongoing discourse regarding the application of grafts to address bone gaps. The aim of this study is the temporal comparison of the radiological and functional outcomes in patients undergoing surgery for intra-articular calcaneal fractures, with a specific focus on the use of bone grafts.

Methods: Thirty patients, comprising 13 with iliac grafts and 17 without, were enrolled in the study.

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Background: Intraoperative ultrasound is becoming a common tool in neurosurgery. However, effective simulation methods are limited. Current, commercial, and homemade phantoms lack replication of anatomical correctness and texture complexity of brain and tumour tissue in ultrasound images.

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Improved deep canonical correlation fusion approach for detection of early mild cognitive impairment.

Med Biol Eng Comput

January 2025

Non-Invasive Imaging and Diagnostic Laboratory, Department of Applied Mechanics and Biomedical Engineering, Indian Institute of Technology Madras, Chennai, India.

Detection of early mild cognitive impairment (EMCI) is clinically challenging as it involves subtle alterations in multiple brain sub-anatomic regions. Among different brain regions, the corpus callosum and lateral ventricles are primarily affected due to EMCI. In this study, an improved deep canonical correlation analysis (CCA) based framework is proposed to fuse magnetic resonance (MR) image features from lateral ventricular and corpus callosal structures for the detection of EMCI condition.

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