Results 281 to 290 of about 29,416,981 (354)

Media images and medical images

Social Science & Medicine (1967), 1975
Abstract The study sought to examine the image of women portrayed in drug advertisements and how that image contrasts with the portrayal of men. Special attention was given to advertisements for mood-modifying drugs since women are the majority of users of such drugs. Content analysis was performed on nearly 500 drug advertisements in a sample drawn
Andrea Mant, Dorothy Broom Darroch
openaire   +2 more sources

Wavelets in medical imaging

AIP Conference Proceedings, 2012
The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact
Siddiqi, A. H., Zahra, Noor E., Sevindir, Huliya A., Aslan, Zafar   +3 more
openaire   +3 more sources

U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation

AAAI Conference on Artificial Intelligence
U-Net has become a cornerstone in various visual applications such as image segmentation and diffusion probability models. While numerous innovative designs and improvements have been introduced by incorporating transformers or MLPs, the networks are ...
Chen-Xin Li, Xinyu Liu, Wu-Yang Li, Cheng Wang, Heng-Yu Liu, Yi-Fan Liu, Zhen Chen, Yixuan Yuan   +7 more
semanticscholar   +1 more source

M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models

arXiv.org
Medical image analysis is essential to clinical diagnosis and treatment, which is increasingly supported by multi-modal large language models (MLLMs). However, previous research has primarily focused on 2D medical images, leaving 3D images under-explored,
Fan Bai, Yu-Xin Du, Tiejun Huang, Max Q.‐H. Meng, Bo Zhao   +4 more
semanticscholar   +1 more source

A Comprehensive Review of U-Net and Its Variants: Advances and Applications in Medical Image Segmentation

IET Image Processing
Medical images often exhibit low and blurred contrast between lesions and surrounding tissues, with considerable variation in lesion edges and shapes even within the same disease, leading to significant challenges in segmentation.
Jiangtao Wang, N. Ruhaiyem, Panpan Fu
semanticscholar   +1 more source

SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation

International Conference on Medical Image Computing and Computer-Assisted Intervention
The Transformer architecture has shown a remarkable ability in modeling global relationships. However, it poses a significant computational challenge when processing high-dimensional medical images. This hinders its development and widespread adoption in
Zhaohu Xing, Tian Ye, Yi-Jun Yang, Guang Liu, Lei Zhu   +4 more
semanticscholar   +1 more source

nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation

International Conference on Medical Image Computing and Computer-Assisted Intervention
The release of nnU-Net marked a paradigm shift in 3D medical image segmentation, demonstrating that a properly configured U-Net architecture could still achieve state-of-the-art results.
Fabian Isensee, Tassilo Wald, Constantin Ulrich, M. Baumgartner, Saikat Roy, K. Maier-Hein, P. Jaeger   +6 more
semanticscholar   +1 more source

Advances in Medical Imaging

Annals of Internal Medicine, 1990
The field of medical imaging, stimulated by advances in digital and communication technologies, has grown tremendously. New imaging techniques that reveal greater anatomical detail are available in most diagnostic radiology departments. We discuss vascular imaging with ultrasound, high-resolution computed tomography of the thorax, magnetic resonance ...
H K, Huang, D R, Aberle, R, Lufkin, E G, Grant, W N, Hanafee, H, Kangarloo   +5 more
openaire   +2 more sources

Segment Anything Model for Medical Image Segmentation: Current Applications and Future Directions

Comput. Biol. Medicine
Due to the inherent flexibility of prompting, foundation models have emerged as the predominant force in the fields of natural language processing and computer vision.
Yichi Zhang, Zhen-Rong Shen, Rushi Jiao
semanticscholar   +1 more source

Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation

arXiv.org
In recent advancements in medical image analysis, Convolutional Neural Networks (CNN) and Vision Transformers (ViT) have set significant benchmarks.
Zi-Yang Wang, Jian-Qing Zheng, Yi-Chi Zhang, Ge Cui, Lei Li   +4 more
semanticscholar   +1 more source