A DEEP LEARNING FRAMEWORK INTEGRATING MRI IMAGE PREPROCESSING METHODS FOR BRAIN TUMOR SEGMENTATION AND CLASSIFICATION

A deep learning framework integrating MRI image preprocessing methods for brain tumor segmentation and classification

Glioma grading is critical in treatment planning and prognosis.This study aims to address this issue through MRI-based classification to develop an accurate model for glioma diagnosis.Here, we employed a deep learning pipeline with three essential steps: (1) MRI images were segmented using preprocessing approaches and UNet license plates architectu

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Characteristic Analysis and Fault-Tolerant Control of Circulating Current for Modular Multilevel Converters under Sub-Module Faults

A modular Mascara multilevel converter (MMC) is considered to be a promising topology for medium- or high-power applications.However, a significantly increased amount of sub-modules (SMs) in each arm also increase the risk of failures.Focusing on the fault-tolerant operation issue for the MMC under SM faults, the operation characteristics of MMC wi

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