Results 71 to 80 of about 340,403 (177)

CapsNet for medical image segmentation

Deep Learning for Medical Image Analysis, Elsevier/Academic Press (accepted)
Tran, Minh, Vo-Ho, Viet-Khoa, Quinn, Kyle, Nguyen, Hien, Luu, Khoa, Le, Ngan   +5 more
openaire   +2 more sources

Brain tumor segmentation based on a hybrid clustering technique

Egyptian Informatics Journal, 2015
Image segmentation refers to the process of partitioning an image into mutually exclusive regions. It can be considered as the most essential and crucial process for facilitating the delineation, characterization, and visualization of regions of interest
Eman Abdel-Maksoud, Mohammed Elmogy, Rashid Al-Awadi   +2 more
doaj   +1 more source

Medical Image Segmentation: A Comprehensive Review of Deep Learning-Based Methods

Tomography
Medical image segmentation is a critical application of computer vision in the analysis of medical images. Its primary objective is to isolate regions of interest in medical images from the background, thereby assisting clinicians in accurately ...
Yuxiao Gao, Yang Jiang, Yanhong Peng, Fujiang Yuan, Xinyue Zhang, Jianfeng Wang   +5 more
doaj   +1 more source

A comparative study on medical image segmentation methods [PDF]

Applied Medical Informatics, 2014
Image segmentation plays an important role in medical images. It has been a relevant research area in computer vision and image analysis. Many segmentation algorithms have been proposed for medical images.
Praylin Selva Blessy SELVARAJ ASSLEY, Helen Sulochana CHELLAKKON   +1 more
doaj  

Boundary Extraction in Images Using Hierarchical Clustering-based Segmentation [PDF]

Hierarchical organization is one of the main characteristics of human segmentation. A human subject segments a natural image by identifying physical objects and marking their boundaries up to a certain level of detail [1].
Selvan, Arul
core  

Segment anything model for medical images?

Medical Image Analysis
Accepted by Medical Image Analysis.
Huang, Yuhao, Yang, Xin, Liu, Lian, Zhou, Han, Chang, Ao, Zhou, Xinrui, Chen, Rusi, Yu, Junxuan, Chen, Jiongquan, Chen, Chaoyu, Liu, Sijing, Chi, Haozhe, Hu, Xindi, Yue, Kejuan, Li, Lei, Grau, Vicente, Fan, Deng-Ping, Dong, Fajin, Ni, Dong   +18 more
openaire   +3 more sources

NAS-Unet: Neural Architecture Search for Medical Image Segmentation

IEEE Access, 2019
Neural architecture search (NAS) has significant progress in improving the accuracy of image classification. Recently, some works attempt to extend NAS to image segmentation which shows preliminary feasibility.
Yu Weng, Tianbao Zhou, Yujie Li, Xiaoyu Qiu   +3 more
doaj   +1 more source

LANet for medical image segmentation

Системный анализ и прикладная информатика
The paper presents an original LANet model for improving medical image segmentation results based on MobileViT neural network. The developed and integrated Efficient Fusion Attention and Adaptive Feature Fusion blocks improve the quality of feature ...
Di Zhao, Yi Tang, D. Y. Pertsau, A. B. Gourinovitch, D. V. Kupryianava   +4 more
doaj   +1 more source

Shortcut Learning in Medical Image Segmentation

Shortcut learning is a phenomenon where machine learning models prioritize learning simple, potentially misleading cues from data that do not generalize well beyond the training set. While existing research primarily investigates this in the realm of image classification, this study extends the exploration of shortcut learning into medical image ...
Manxi Lin, Nina Weng, Kamil Mikolaj, Zahra Bashir, Morten B. S. Svendsen, Martin G. Tolsgaard, Anders N. Christensen, Aasa Feragen   +7 more
openaire   +3 more sources

AdaptiveConv2d: A Novel Convolutional Module for Medical Image Segmentation

Applied Sciences
With the rapid advancement of medical imaging technology, medical image segmentation has become increasingly crucial in disease diagnosis, treatment planning, and intraoperative navigation.
Donghua Liu, Zuofeng Zhou
doaj   +1 more source