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Enhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning.

Comput Biol Med

January 2025

Emerging Technologies Research Lab (ETRL), College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia; Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia. Electronic address:

- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmentation, yet misdiagnoses yield effective medical responses, impacting patient survival rates. Recent technological advancements have popularized deep learning-based medical image analysis, leveraging transfer learning to reuse pre-trained models for various applications.

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Hyperpolarized-C magnetic resonance imaging (HP-C MRI) was used to image changes in C-lactate signal during a visual stimulus condition in comparison to an eyes-closed control condition. Whole-brain C-pyruvate, C-lactate and C-bicarbonate production was imaged in healthy volunteers (N = 6, ages 24-33) for the two conditions using two separate hyperpolarized C-pyruvate injections. BOLD-fMRI scans were used to delineate regions of functional activation.

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Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monitor real-time changes in cerebral hemodynamics. In this study, thirty-six healthy adults were measured by single channel fNIRS to explore differences between two age groups using machine learning (ML). The subjects, measured during functional magnetic resonance imaging (fMRI) at Oulu University Hospital, were divided into young (age ≤ 32) and elderly (age ≥ 57) groups.

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Background: This study aimed to explore the relationship of cervical tumor lesion location (CTLL) with bilateral parametrial involvement (PI) and pelvic lymph node metastasis (LNM).

Methods: The study retrospectively analyzed the clinicopathologic and imaging data of patients with cervical squamous cell carcinoma (SCC) retrieved from multiple centers. According to the CTLL, patients were allocated to three groups: a middle one third group, a unilaterally dominant group, and the entire-region group.

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The purpose of this study is to evaluate the effectiveness of intensity-modulated radiation therapy (IMRT) combined with periorbital triamcinolone acetonide injection in treating thyroid eye disease (TED) patients with active extraocular muscle but low CAS. The retrospective observational study was conducted. A total of 156 eligible patients were selected from the TED patient database of the Ophthalmology Department of West China Hospital of Sichuan University.

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