Results 271 to 280 of about 151,110 (308)
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2019
Today, IoT in therapeutic administrations has ended up being more productive in light of the fact that the correspondence among authorities and patients has been improved with versatile applications. These applications are made by the associations with the objective that the pros can screen the patient's prosperity.
Ramgopal Kashyap, Surendra Rahamatkar
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Today, IoT in therapeutic administrations has ended up being more productive in light of the fact that the correspondence among authorities and patients has been improved with versatile applications. These applications are made by the associations with the objective that the pros can screen the patient's prosperity.
Ramgopal Kashyap, Surendra Rahamatkar
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SEGMENTATION OF MEDICAL IMAGES
Herald of Khmelnytskyi National University. Technical sciences, 2020Segmentation is an integral part of the digital image processing process. It is the division or division of the image into some parts that meet the specified characteristics and characterize these areas and the image as a whole. At the segmentation stage, issues are solved that complement the standard tasks of image processing, namely coding ...
V. MOSTOVYI, S. HORIASHCHENKO
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Segmentation of medical images using LEGION
IEEE Transactions on Medical Imaging, 1999Advances in visualization technology and specialized graphic workstations allow clinicians to virtually interact with anatomical structures contained within sampled medical-image datasets. A hindrance to the effective use of this technology is the difficult problem of image segmentation.
N, Shareef, D L, Wang, R, Yagel
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Dynamic domain generalization for medical image segmentation
Neural Networks, 2023Domain Generalization-based Medical Image Segmentation (DGMIS) aims to enhance the robustness of segmentation models on unseen target domains by learning from fully annotated data across multiple source domains. Despite the progress made by traditional DGMIS methods, they still face several challenges. First, most DGMIS approaches rely on static models
Zhiming Cheng +3 more
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Current Methods in Medical Image Segmentation
Annual Review of Biomedical Engineering, 2000▪ Abstract  Image segmentation plays a crucial role in many medical-imaging applications, by automating or facilitating the delineation of anatomical structures and other regions of interest. We present a critical appraisal of the current status of semiautomated and automated methods for the segmentation of anatomical medical images.
D L, Pham, C, Xu, J L, Prince
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Soft thresholding for medical image segmentation
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 2010A new soft thresholding method is presented. The method is based on relating each pixel in the image to the different regions via a membership function, rather than through hard decisions. The membership function of each of the regions is derived from the histogram of the image.
Santiago, Aja-Fernandez +2 more
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Novel segmentation algorithm in segmenting medical images
Journal of Systems and Software, 2010The aim of this paper is to develop an effective fuzzy c-means (FCM) technique for segmentation of Magnetic Resonance Images (MRI) which is seriously affected by intensity inhomogeneities that are created by radio-frequency coils. The weighted bias field information is employed in this work to deal the intensity inhomogeneities during the segmentation ...
S.R. Kannan +3 more
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[Medical image segmentation techniques].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2007Medical image segmentation is an important application of image segmentation. However it is the bottleneck that restrains medical image application in clinical practice. In this paper, the aim and significance of medical image segmentation are discussed, the development of medical image segmentation techniques is sketched, and a review of the medical ...
Jing, Li, Shan'an, Zhu, He, Bin
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Medical Image Segmentation Using Genetic Algorithms
IEEE Transactions on Information Technology in Biomedicine, 2009Genetic algorithms (GAs) have been found to be effective in the domain of medical image segmentation, since the problem can often be mapped to one of search in a complex and multimodal landscape. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries.
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Medical Image Segmentation Techniques
Medical image segmentation is a critical task in medical imaging that involves delineating structures of interest within medical images, such as organs, tissues, and abnormalities. The accuracy and efficiency of segmentation directly impact the quality of medical care, making it a pivotal component in modern healthcare.Anju Shukla +3 more
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