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Image segmentation using deep learning: A survey
Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …
applications such as scene understanding, medical image analysis, robotic perception …
A comprehensive review of modern object segmentation approaches
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 …
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 …
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
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 …
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 …
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
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 …
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 …
that requires the accurate delineation of multiple building instances over typically large …
[PDF][PDF] An overview of intelligent image segmentation using active contour models
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 …
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 …
osteosarcoma. With the improvement of hardware technology and computing power …
Affinity feature strengthening for accurate, complete and robust vessel segmentation
Vessel segmentation is crucial in many medical image applications, such as detecting
coronary stenoses, retinal vessel diseases and brain aneurysms. However, achieving high …
coronary stenoses, retinal vessel diseases and brain aneurysms. However, achieving high …