Results 31 to 40 of about 6,546,529 (270)

UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation [PDF]

IEEE Transactions on Medical Imaging, 2019
The state-of-the-art models for medical image segmentation are variants of U-Net and fully convolutional networks (FCN). Despite their success, these models have two limitations: (1) their optimal depth is apriori unknown, requiring extensive ...
Zongwei Zhou, M. R. Siddiquee, Nima Tajbakhsh, Jianming Liang   +3 more
semanticscholar   +1 more source

MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation [PDF]

International Conference on Medical Image Computing and Computer-Assisted Intervention, 2023
There has been exploding interest in embracing Transformer-based architectures for medical image segmentation. However, the lack of large-scale annotated medical datasets make achieving performances equivalent to those in natural images challenging ...
Saikat Roy, Gregor Koehler, Constantin Ulrich, M. Baumgartner, Jens Petersen, Fabian Isensee, P. Jaeger, K. Maier-Hein   +7 more
semanticscholar   +1 more source

OneFormer: One Transformer to Rule Universal Image Segmentation [PDF]

Computer Vision and Pattern Recognition, 2022
Universal Image Segmentation is not a new concept. Past attempts to unify image segmentation include scene parsing, panoptic segmentation, and, more recently, new panoptic architectures.
Jitesh Jain, Jiacheng Li, M. Chiu, Ali Hassani, Nikita Orlov, Humphrey Shi   +5 more
semanticscholar   +1 more source

Image quality and segmentation [PDF]

Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 2018
Algorithms for image segmentation (including object recognition and delineation) are influenced by the quality of object appearance in the image and overall image quality. However, the issue of how to perform segmentation evaluation as a function of these quality factors has not been addressed in the literature.
Drew A. Torigian, Charles B. Simone, Jayaram K. Udupa, Yubing Tong, Gargi Pednekar, David J. McLaughlin, Xingyu Wu, Joseph Camaratta   +7 more
openaire   +3 more sources

Binocular Image Segmentation Based on Graph Cuts Multi-feature Selection [PDF]

Jisuanji kexue, 2021
Binocular image segmentation is crucial for subsequent applications such as stereoscopic object synthesis and 3D reconstruction.Since binocular images contain scene depth information,it is difficult to obtain ideal segmentation results by applying ...
JIN Hai-yan, PENG Jing, ZHOU Ting, XIAO Zhao-lin
doaj   +1 more source

Medical Image Segmentation Review: The Success of U-Net [PDF]

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Automatic medical image segmentation is a crucial topic in the medical domain and successively a critical counterpart in the computer-aided diagnosis paradigm. U-Net is the most widespread image segmentation architecture due to its flexibility, optimized
Reza Azad, Ehsan Khodapanah Aghdam, Amelie Rauland, Yiwei Jia, Atlas Haddadi Avval, Afshin Bozorgpour, Sanaz Karimijafarbigloo, J. P. Cohen, E. Adeli, D. Merhof   +9 more
semanticscholar   +1 more source

Capsules for biomedical image segmentation

Medical Image Analysis, 2021
Our work expands the use of capsule networks to the task of object segmentation for the first time in the literature. This is made possible via the introduction of locally-constrained routing and transformation matrix sharing, which reduces the parameter/memory burden and allows for the segmentation of objects at large resolutions.
Rodney LaLonde, Ziyue Xu, Ismail Irmakci, Sanjay Jain, Ulas Bagci   +4 more
openaire   +5 more sources

Estimation of Depth Information of Image Based on Energy Distribution

Chemical Engineering Transactions, 2015
Image segmentation is an effective way to analysis image, which has received more and more attention. The traditional image segmentation technology can't get the result of the semantic image segmentation.
J.Y. Li, Q.B. Yuan
doaj   +1 more source

Retracted: Active Contour Image Segmentation Method for Training Talents of Computer Graphics and Image Processing Technology

IEEE Access, 2021
Image segmentation is a key technology in the field of computer image processing. Among them, segmentation methods based on active contour models have been developed rapidly in recent years due to their effective processing of complex images such as ...
Xinghuo Ye, Qianyi Wang
doaj   +1 more source

Segmentation of multi-temporal polarimetric SAR data based on mean-shift and spectral graph partitioning [PDF]

PeerJ, 2022
Polarimetric SAR (PolSAR) image segmentation is a key step in its interpretation. For the targets with time series changes, the single-temporal PolSAR image segmentation algorithm is difficult to provide correct segmentation results for its target ...
Caiqiong Wang, Lei Zhao, Wangfei Zhang, Xiyun Mu, Shitao Li   +4 more
doaj   +2 more sources