机构

• 长春光学精密机械与物... [1]
• 自动化研究所 [1]
• 合肥物质科学研究院 [1]

采集方式

• OAI收割 [3]

_filter

_filter

_filter

筛选

浏览/检索结果: 共3条，第1-3条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Exploring Schizophrenia Classification Through Multimodal MRI and Deep Graph Neural Networks: Unveiling Brain Region-Specific Weight Discrepancies and Their Association With Cell-Type Specific Transcriptomic Features 期刊论文  OAI收割 SCHIZOPHRENIA BULLETIN, 2024, 页码: 19 作者:  Gao, Jingjing;  Qian, Maomin;  Wang, Zhengning;  Li, Yanling;  Luo, Na   |  收藏  |  浏览/下载：17/0  |  提交时间：2024/07/03 schizophrenia identification  multimodal MRI  deep graph neural networks  image marker  gene analysis   A feasibility study of dynamic verification for tumor target delineation and dose delivery using a six degrees of freedom motion phantom 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF RADIATION RESEARCH, 2018, 卷号: 16, 期号: 4, 页码: 411-420 作者:  Xu, G.;  Xiong, Z.;  Wang, H.;  Jiang, H.;  Li, B.   |  收藏  |  浏览/下载：18/0  |  提交时间：2020/05/21 6DOF dynamic phantom  respiratory motion  image artifacts  dose verification  external marker tracking   A new segmentation method of CR images based on discrete wavelet transform and mathematics morphology (EI CONFERENCE) 会议论文  OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者:  Li Z.;  Li Z. 收藏  |  浏览/下载：68/0  |  提交时间：2013/03/25 In this paper  we propose a segmentation method of CR(computed radiography) images with being rid of under-segmentation and over-segmentation. An under-segmentation occurs when pixels belonging to different objects are grouped into a single region. Such errors are the most dangerous because they can invalidate the whole segmentation process. The phenomenon always takes place when we segment CR images because of the principle of CR. In order to depressed under-segmentation  we enhance the CR images using DWT (discrete wavelet transform) to get more detail of CR image features. As we enhance the CR image  the over-segmentation maybe occurs. Compared with under-segmentation  the over-segmentation occurs when a single objects is subdivided by segmentation into several region. For the purpose of preventing from the over-segmentation  we present a scheme for enhanced CR images based on watershed algorithm that solves over-segmentation problem. We use marker-based watershed algorithm. Together with gradient image and marker image  watershed segmentation can make sure to partition CR image into meaningful object and avoid further segmentation of homogeneous regions. The result of the proposed algorithm are compared with those of other standard methods. Experiments have shown a better result and indeed solved under-segmentation and over-segmentation problems.