Results 41 to 50 of about 488,489 (323)
A Review of Medical Image Segmentation Algorithms [PDF]
EAI Endorsed Transactions on Pervasive Health and Technology, 2021 INTRODUCTION: Image segmentation in medical physics plays a vital role in image analysis to identify the affected tumour. The process of subdividing an image into its constituent parts that are homogeneous in feature is ...
K.K.D. Ramesh +4 more
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Treatment planning with a 2.5 MV photon beam for radiation therapy
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Purpose The shallow depth of maximum dose and higher dose fall‐off gradient of a 2.5 MV beam along the central axis that is available for imaging on linear accelerators is investigated for treatment of shallow tumors and sparing the organs at risk (OARs) beyond it.
Navid Khaledi +5 more
wiley +1 more source
IEEE Access, 2020 The emergence of 4D heart images makes the data volume of the images multiply. It is more urgent to require an effective and fast segmentation algorithm.
Hui Liu, Wen Chu, Hua Wang
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Segmentation Ability Map: Interpret deep features for medical image segmentation [PDF]
Medical Image Analysis, 2023, 2022 Deep convolutional neural networks (CNNs) have been widely used for medical image segmentation. In most studies, only the output layer is exploited to compute the final segmentation results and the hidden representations of the deep learned features have not been well understood.
arxiv
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract This study aims to investigate the effects of the position correction of size‐specific dose estimates (SSDE) on patient dose estimation in cone beam computed tomography (CBCT). The relationship between the phantom position and absorbed dose in the right breast was studied using optically stimulated luminescence dosimeters and a simulated human
Hiroyuki Ueno +3 more
wiley +1 more source
WAILS: Watershed Algorithm With Image-Level Supervision for Weakly Supervised Semantic Segmentation
IEEE Access, 2019 Image semantic segmentation has great development in many fields, and the lack of fully supervised segmentation labels has always been a major problem in the development of image semantic segmentation.
Hongming Zhou +4 more
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Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract The present study was conducted as part of a comprehensive work to establish National Diagnostic Reference Levels (NDRLs) in Sri Lanka for the first time. DRLs can be used as an effective optimization tool for identifying unusually high or low patient doses during X‐ray examinations.
Sachith Welarathna +3 more
wiley +1 more source
Oil Spill SAR Image Segmentation via Probability Distribution Modelling [PDF]
arXiv, 2021 Segmentation of marine oil spills in Synthetic Aperture Radar (SAR) images is a challenging task because of the complexity and irregularities in SAR images. In this work, we aim to develop an effective segmentation method which addresses marine oil spill identification in SAR images by investigating the distribution representation of SAR images.
arxiv
Evolutionary image segmentation [PDF]
, 1997 We describe an approach to image segmentation based on a two-layer module that is executed until a good segmentation is achieved, providing an evolution of previous segmentation results at each execution. The first layer performs a global segmentation of an image of decreasing area at each evolution by adopting a genetic algorithm learning technique to
Zingaretti P., Carbonaro A., Puliti P.
openaire +3 more sources
IMAGE SEGMENTATION AND OBJECT RECOGNITION BASED ON CONVOLUTIONAL NEURAL NETWORK TECHNOLOGY
Надежность и качество сложных систем, 2021 Background. An analysis of the processes of image segmentation is being carried out. An original method of image segmentation using a convolutional neural network is proposed. Materials and methods.
A.I. Godunov, S.T. Balanyan, P.S. Egorov
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