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Cerebrovascular Segmentation Model Based on Spatial Attention-Guided 3D Inception U-Net with Multi-Directional MIPs

https://doi.org/10.3390/app12052288

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Random 2.5D U-net for Fully 3D Segmentation

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JointVesselNet: Joint Volume-Projection Convolutional Embedding Networks for 3D Cerebrovascular Segmentation

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A New Parallel Thinning Algorithm with Stroke Correction for Odia Characters

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U-Net: Convolutional Networks for Biomedical Image Segmentation

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DeepVessel: Retinal Vessel Segmentation via Deep Learning and Conditional Random Field

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3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation

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Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation

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Snakes: Active contour models

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Detection of peritoneal dissemination in gynecological malignancy: evaluation by diffusion-weighted MR imaging

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Vessel enhancement filter using directional filter bank

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A level set method based on additive bias correction for image segmentation

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Watershed and multimodal data for brain vessel segmentation: Application to the superior sagittal sinus

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Widening and Rotation of Carotid Artery with Age: Geometric Approach

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Active contours driven by region-scalable fitting and optimized Laplacian of Gaussian energy for image segmentation

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Active contours driven by adaptive functions and fuzzy c-means energy for fast image segmentation

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Evaluation of Hessian-based filters to enhance the axis of coronary arteries in CT images

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MRI-induced stimulation of peripheral nerves: dependency of stimulation threshold on patient positioning

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Improved minimum intensity projection in holographic reconstruction via SNR-enhanced holography

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Linear time Euclidean distance transform algorithms

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Rethinking the Inception Architecture for Computer Vision

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Bag of Tricks for Image Classification with Convolutional Neural Networks

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ITK-SNAP: An interactive tool for semi-automatic segmentation of multi-modality biomedical images

inferredcites →https://doi.org/10.1109/isbi.2019.8759569openalex-snapshot

Cerebrovascular Network Segmentation of MRA Images With Deep Learning

inferredcites →https://doi.org/10.1109/isbi48211.2021.9433777openalex-snapshot

2d-3d Hierarchical Feature Fusion Network For Segmentation Of Bone Structure In Knee Mr Image

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Projection-Based 2.5D U-net Architecture for Fast Volumetric Segmentation

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COVID-view: Diagnosis of COVID-19 using Chest CT

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Distance Transform Gradient Density Estimation Using the Stationary Phase Approximation

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Jump flooding in GPU with applications to Voronoi diagram and distance transform

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2D Euclidean distance transform algorithms

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Use of maximum intensity projections in CT angiography: a basic review.

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Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

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Effect of Slab Thickness on the CT Detection of Pulmonary Nodules: Use of Sliding Thin-Slab Maximum Intensity Projection and Volume Rendering

inferredcites →https://doi.org/10.4304/jcp.8.11.3012-3019openalex-snapshot

A Novel Thinning Algorithm of 3D Image Model Based on Spatial Wavelet Interpolation

inferredcites →https://doi.org/10.48550/arxiv.1612.00593openalex-snapshot

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

inferredcites →https://doi.org/10.5121/ijma.2013.5201openalex-snapshot

Improved Parallel Thinning Algorithm to Obtain Unit-Width Skeleton

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Basilar Artery Angulation in Association with Aging and Pontine Lacunar Infarction: A Multicenter Observational Study

inferredcites →https://doi.org/10.7910/dvn/tiofr2openalex-snapshot

Synthetic Vasculature Datsets

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Segmentation of Cerebral Vessels in Mouse Tof-Mra Via an Attention-Based Multi-Kernel Convolutional Network with Multiscale Vessel Enhancement

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Deep learning technology in vascular image segmentation and disease diagnosis

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CNN-Based Quantification of Blood Vessels Lumen in 3D Images

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Medical image data augmentation: techniques, comparisons and interpretations

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Spatial multi-scale attention U-improved network for blood vessel segmentation

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Multi-scale Knowledge Transfer Vision Transformer for 3D vessel shape segmentation

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SIAM: Spatial and Intensity Awareness Module for cerebrovascular segmentation

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On efficient expanding training datasets of breast tumor ultrasound segmentation model

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All answers are in the images: A review of deep learning for cerebrovascular segmentation

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PGFC-Net: Parallel-Encoding Gaussian Feature Coordination-Enhanced Network for accurate 3D hepatic vessel and inferior vena cava segmentation

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Brain Vessel Segmentation Using Deep Learning—A Review

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Intelligent Robotic Motion Copying System LevshAi for Neurosurgical Endovascular Operations with Haptic Feedback and Preoperative Personalized Simulation

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Preoperative Personalized Vascular 3D Simulator of the Intelligent Robotic Ecosystem LevshAI for Endovascular Neurosurgery

inferred← citeshttps://doi.org/10.1109/icicml60161.2023.10424857openalex-snapshot

Segmentation of Cerebral Vessels in Mouse TOF-MRA by an Attention Network

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Top-K Maximum Intensity Projection Priors for 3D Liver Vessel Segmentation

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Knee cartilage MR images segmentation based on multi-dimensional hybrid convolutional neural network

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High Performing Facial Skin Problem Diagnosis with Enhanced Mask R-CNN and Super Resolution GAN

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Using Deep Learning and B-Splines to Model Blood Vessel Lumen from 3D Images

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