Diverticulum
发表于 2025-3-21 18:00:59
书目名称Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0190322<br><br> <br><br>书目名称Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0190322<br><br> <br><br>书目名称Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0190322<br><br> <br><br>书目名称Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0190322<br><br> <br><br>书目名称Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0190322<br><br> <br><br>书目名称Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0190322<br><br> <br><br>书目名称Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0190322<br><br> <br><br>书目名称Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0190322<br><br> <br><br>书目名称Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0190322<br><br> <br><br>书目名称Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0190322<br><br> <br><br>
热情的我
发表于 2025-3-21 22:12:06
978-3-030-46642-8Springer Nature Switzerland AG 2020
精密
发表于 2025-3-22 03:47:13
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FLIP
发表于 2025-3-22 05:32:26
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CRASS
发表于 2025-3-22 11:23:14
,Programmierung für Fortgeschrittene,, because manual practices of segmenting tumors are time consuming, expensive and can be subject to clinician diagnostic error. We propose a novel neuromorphic attention-based learner (NABL) model to train the deep neural network for tumor segmentation, which is with challenges of typically small da
撕裂皮肉
发表于 2025-3-22 12:56:57
Macromedia Director für Durchstarter. Despite their prevalence, deep learning-based segmentation methods, which usually use multiple MR sequences as input, still have limited performance, partly due to their insufficient ability to image representation. In this paper, we propose a brain tumor segmentation (BraTSeg) model, which uses c
atopic-rhinitis
发表于 2025-3-22 18:43:22
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发出眩目光芒
发表于 2025-3-23 00:03:54
Norbert Welsch,Frank von Kuhlberg most common primary malignant tumors with different degrees of invasion. The segmentation of brain tumors is a prerequisite for disease diagnosis, surgical planning and prognosis. According to the characteristics of brain tumor data, we designed a multi-model fusion brain tumor automatic segmentati
会犯错误
发表于 2025-3-23 03:16:56
Norbert Welsch,Frank von Kuhlbergmetric magnetic resonance images (mpMRI) is of great clinical importance, which defines tumour size, shape and appearance and provides abundant information for preoperative diagnosis, treatment planning and survival prediction. Recent developments on deep learning have significantly improved the per
MUMP
发表于 2025-3-23 06:35:39
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