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 …
Modeling of deformable objects for robotic manipulation: A tutorial and review
Manipulation of deformable objects has given rise to an important set of open problems in
the field of robotics. Application areas include robotic surgery, household robotics …
the field of robotics. Application areas include robotic surgery, household robotics …
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 …
Kidney tumor semantic segmentation using deep learning: A survey of state-of-the-art
A Abdelrahman, S Viriri - Journal of imaging, 2022 - mdpi.com
Cure rates for kidney cancer vary according to stage and grade; hence, accurate diagnostic
procedures for early detection and diagnosis are crucial. Some difficulties with manual …
procedures for early detection and diagnosis are crucial. Some difficulties with manual …
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 …
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 …
TUnet-LBF: Retinal fundus image fine segmentation model based on transformer Unet network and LBF
H Zhang, W Ni, Y Luo, Y Feng, R Song… - Computers in Biology and …, 2023 - Elsevier
Segmentation of retinal fundus images is a crucial part of medical diagnosis. Automatic
extraction of blood vessels in low-quality retinal images remains a challenging problem. In …
extraction of blood vessels in low-quality retinal images remains a challenging problem. In …
Image segmentation review: Theoretical background and recent advances
Image segmentation is a significant topic in image refining and automated image analysis
with relevance for instance object recognition, diagnostic imaging scanning, mechanized …
with relevance for instance object recognition, diagnostic imaging scanning, mechanized …
A coarse-to-fine segmentation frame for polyp segmentation via deep and classification features
Accurate polyp segmentation is of great significance for the diagnosis and treatment of colon
cancer. Deep convolution network can extract the common high level features of the target …
cancer. Deep convolution network can extract the common high level features of the target …
End-to-end boundary aware networks for medical image segmentation
A Hatamizadeh, D Terzopoulos… - Machine Learning in …, 2019 - Springer
Fully convolutional neural networks (CNNs) have proven to be effective at representing and
classifying textural information, thus transforming image intensity into output class masks …
classifying textural information, thus transforming image intensity into output class masks …