[HTML][HTML] A review: Deep learning for medical image segmentation using multi-modality fusion
Multi-modality is widely used in medical imaging, because it can provide multiinformation
about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing …
about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing …
[HTML][HTML] A review on brain tumor segmentation based on deep learning methods with federated learning techniques
Brain tumors have become a severe medical complication in recent years due to their high
fatality rate. Radiologists segment the tumor manually, which is time-consuming, error …
fatality rate. Radiologists segment the tumor manually, which is time-consuming, error …
IVD-Net: Intervertebral disc localization and segmentation in MRI with a multi-modal UNet
Accurate localization and segmentation of intervertebral disc (IVD) is crucial for the
assessment of spine disease diagnosis. Despite the technological advances in medical …
assessment of spine disease diagnosis. Despite the technological advances in medical …
Dense multi-path U-Net for ischemic stroke lesion segmentation in multiple image modalities
Dense Multi-path U-Net for Ischemic Stroke Lesion Segmentation in Multiple Image Modalities
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Chest X-ray image phase features for improved diagnosis of COVID-19 using convolutional neural network
X Qi, LG Brown, DJ Foran, J Nosher… - International journal of …, 2021 - Springer
Purpose: Recently, the outbreak of the novel coronavirus disease 2019 (COVID-19)
pandemic has seriously endangered human health and life. In fighting against COVID-19 …
pandemic has seriously endangered human health and life. In fighting against COVID-19 …
MM-BiFPN: multi-modality fusion network with Bi-FPN for MRI brain tumor segmentation
For medical imaging tasks, it is a prevalent practice to have a multi-modality image dataset,
as experts prefer using multiple medical devices to diagnose a disease. Each device can …
as experts prefer using multiple medical devices to diagnose a disease. Each device can …
AATSN: Anatomy Aware Tumor Segmentation Network for PET-CT volumes and images using a lightweight fusion-attention mechanism
Abstract Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) provides metabolic
information, while Computed Tomography (CT) provides the anatomical context of the …
information, while Computed Tomography (CT) provides the anatomical context of the …
MM-UNet: A multimodality brain tumor segmentation network in MRI images
The global annual incidence of brain tumors is approximately seven out of 100,000,
accounting for 2% of all tumors. The mortality rate ranks first among children under 12 and …
accounting for 2% of all tumors. The mortality rate ranks first among children under 12 and …
[HTML][HTML] Recognition of pollution layer location in 11 kV polymer insulators used in smart power grid using dual-input VGG Convolutional Neural Network
This paper portrays the application of a Partial Discharge (PD) signal combined with the
dual-input VGG Convolution Neural Network (CNN) to predict the location of the pollution …
dual-input VGG Convolution Neural Network (CNN) to predict the location of the pollution …