Image segmentation using deep learning: A survey

S Minaee, Y Boykov, F Porikli, A Plaza… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …

A comprehensive review of modern object segmentation approaches

Y Wang, U Ahsan, H Li, M Hagen - Foundations and Trends® …, 2022 - nowpublishers.com
Image segmentation is the task of associating pixels in an image with their respective object
class labels. It has a wide range of applications in many industries including healthcare …

clDice-a novel topology-preserving loss function for tubular structure segmentation

S Shit, JC Paetzold, A Sekuboyina… - Proceedings of the …, 2021 - openaccess.thecvf.com
Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or
roads, is relevant to many fields of research. For such structures, the topology is their most …

Anatomy-aided deep learning for medical image segmentation: a review

L Liu, JM Wolterink, C Brune… - Physics in Medicine & …, 2021 - iopscience.iop.org
Deep learning (DL) has become widely used for medical image segmentation in recent
years. However, despite these advances, there are still problems for which DL-based …

[HTML][HTML] Research on artificial-intelligence-assisted medicine: a survey on medical artificial intelligence

F Gou, J Liu, C **ao, J Wu - Diagnostics, 2024 - mdpi.com
With the improvement of economic conditions and the increase in living standards, people's
attention in regard to health is also continuously increasing. They are beginning to place …

State-of-the-art review of machine learning applications in additive manufacturing; from design to manufacturing and property control

GK Sarkon, B Safaei, MS Kenevisi, S Arman… - … Methods in Engineering, 2022 - Springer
In this review, some of the latest applicable methods of machine learning (ML) in additive
manufacturing (AM) have been presented and the classification of the most common ML …

End-to-end trainable deep active contour models for automated image segmentation: Delineating buildings in aerial imagery

A Hatamizadeh, D Sengupta, D Terzopoulos - Computer Vision–ECCV …, 2020 - Springer
The automated segmentation of buildings in remote sensing imagery is a challenging task
that requires the accurate delineation of multiple building instances over typically large …

[PDF][PDF] An overview of intelligent image segmentation using active contour models

Y Chen, P Ge, G Wang, G Weng, H Chen - Intell. Robot, 2023 - researchgate.net
The active contour model (ACM) approach in image segmentation is regarded as a research
hotspot in the area of computer vision, which is widely applied in different kinds of …

[HTML][HTML] A multimodal auxiliary classification system for osteosarcoma histopathological images based on deep active learning

F Gou, J Liu, J Zhu, J Wu - Healthcare, 2022 - mdpi.com
Histopathological examination is an important criterion in the clinical diagnosis of
osteosarcoma. With the improvement of hardware technology and computing power …

Affinity feature strengthening for accurate, complete and robust vessel segmentation

T Shi, X Ding, W Zhou, F Pan, Z Yan… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Vessel segmentation is crucial in many medical image applications, such as detecting
coronary stenoses, retinal vessel diseases and brain aneurysms. However, achieving high …