Results 31 to 40 of about 170,175 (308)

Multiresolution analysis using wavelet, ridgelet, and curvelet transforms for medical image segmentation [PDF]

, 2011
Copyright @ 2011 Shadi AlZubi et al. This article has been made available through the Brunel Open Access Publishing Fund.The experimental study presented in this paper is aimed at the development of an automatic image segmentation system for classifying ...
Alzubi, S, Maysam Abbod, Naveed Islam, Abbod, MF, Shadi AlZubi, Islam, N   +5 more
core   +1 more source

Digital Medical Image Segmentation Using Fuzzy C-Means Clustering

UHD Journal of Science and Technology, 2020
In the modern globe, digital medical image processing is a major branch to study in the fields of medical and information technology. Every medical field relies on digital medical imaging in diagnosis for most of their cases.
Bakhtyar Ahmed Mohammed, Muzhir Shaban Al-Ani   +1 more
doaj   +1 more source

Semi-supervised Learning for Real-time Segmentation of Ultrasound Video Objects: A Review [PDF]

Advanced Ultrasound in Diagnosis and Therapy, 2023
Real-time intelligent segmentation of ultrasound video object is a demanding task in the field of medical image processing and serves as an essential and critical step in image-guided clinical procedures.
Jin Guo, MD, Zhaojun Li, PhD, Yanping Lin, PhD
doaj   +1 more source

Brain Image Segmentation Based on Fuzzy Clustering

Al-Mustansiriyah Journal of Science, 2018
The segmentation performance is topic to suitable initialization and best configuration of supervisory parameters. In medical image segmentation, the segmentation is very important when the diagnosing becomes very hard in medical images which are not ...
Mohammed Y. Kamil
doaj   +1 more source

Facial soft tissue segmentation [PDF]

, 2014
The importance of the face for socio-ecological interaction is the cause for a high demand on any surgical intervention on the facial musculo-skeletal system.
Majeed, Tahir
core   +1 more source

How interaction methods affect image segmentation: user experience in the task [PDF]

, 2013
Interactive image segmentation is extensively used in photo editing when the aim is to separate a foreground object from its background so that it is available for various applications.
Healy, Graham, McGuinness, Kevin, Hebbalaguppe, Ramya, G. Healy, Alan Smeaton, K. McGuinness, O'Connor, Noel E., Noel O'Connor, Smeaton, Alan F., Kuklyte, Jogile, O\u27Connor, Noel E., R. Hebbalaguppe, J. Kuklyte   +12 more
core   +1 more source

MIScnn: a framework for medical image segmentation with convolutional neural networks and deep learning

BMC Medical Imaging, 2021
Background The increased availability and usage of modern medical imaging induced a strong need for automatic medical image segmentation. Still, current image segmentation platforms do not provide the required functionalities for plain setup of medical ...
Dominik Müller, Frank Kramer
doaj   +1 more source

Multi-scale Gaussian representation and outline-learning based cell image segmentation [PDF]

, 2013
BACKGROUND: High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies.
Rämö, P., Mario Emmenlauer, Ruusuvuori, P., Pekka Ruusuvuori, Dehio, C., Yli-Harja, O., Christoph Dehio, Emmenlauer, M., Olli Yli-Harja, Farhan, M., Muhammad Farhan, Pauli Rämö   +11 more
core   +1 more source

Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation [PDF]

, 2020
Although having achieved great success in medical image segmentation, deep learning-based approaches usually require large amounts of well-annotated data, which can be extremely expensive in the field of medical image analysis.
Yu, Zhiding, Liu, Fengze, Yu, Lequan, Yuille, Alan, Cai, Jinzheng, Xu, Daguang, Zhu, Zhuotun, Xia, Yingda, Yang, Dong, Roth, Holger   +9 more
core   +1 more source

DCSLK: Combined large kernel shared convolutional model with dynamic channel Sampling

NeuroImage
This study centers around the competition between Convolutional Neural Networks (CNNs) with large convolutional kernels and Vision Transformers in the domain of computer vision, delving deeply into the issues pertaining to parameters and computational ...
Zongren Li, Shuping Luo, Hongwei Li, Yanbin Li   +3 more
doaj   +1 more source