{"title":"修正“一种新型卷积神经网络用于多发性硬化症脑损伤自动分割”。","authors":"","doi":"10.1111/jon.70093","DOIUrl":null,"url":null,"abstract":"<p>E Dereskewicz, F La Rosa, J Dos Santos Silva, et al. “A Novel Convolutional Neural Network for Automated Multiple Sclerosis Brain Lesion Segmentation.” <i>Journal of Neuroimaging</i> 35.5 (2025): e70085.</p><p>In Table 7, the text “dawm” was a typo and should have been removed. In addition, the table should present all values with two significant figures.</p><p>We apologize for this error.</p><p>Table 7. Performance comparison between 2D and 3D scans in the clinical dataset across all models.\n\n </p><p><i>Note</i>: Average values across five subjects are provided for each metric.</p><p>Abbreviations: LFPR, lesion false positive rate; LTPR, lesion true positive rate; RVD, relative volume difference.</p>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 5","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jon.70093","citationCount":"0","resultStr":"{\"title\":\"Correction to “A Novel Convolutional Neural Network for Automated Multiple Sclerosis Brain Lesion Segmentation”\",\"authors\":\"\",\"doi\":\"10.1111/jon.70093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>E Dereskewicz, F La Rosa, J Dos Santos Silva, et al. “A Novel Convolutional Neural Network for Automated Multiple Sclerosis Brain Lesion Segmentation.” <i>Journal of Neuroimaging</i> 35.5 (2025): e70085.</p><p>In Table 7, the text “dawm” was a typo and should have been removed. In addition, the table should present all values with two significant figures.</p><p>We apologize for this error.</p><p>Table 7. Performance comparison between 2D and 3D scans in the clinical dataset across all models.\\n\\n </p><p><i>Note</i>: Average values across five subjects are provided for each metric.</p><p>Abbreviations: LFPR, lesion false positive rate; LTPR, lesion true positive rate; RVD, relative volume difference.</p>\",\"PeriodicalId\":16399,\"journal\":{\"name\":\"Journal of Neuroimaging\",\"volume\":\"35 5\",\"pages\":\"\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2025-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jon.70093\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Neuroimaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/jon.70093\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Neuroimaging","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jon.70093","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
摘要
E Dereskewicz, F La Rosa, J Dos Santos Silva等,“用于多发性硬化症脑损伤自动分割的新型卷积神经网络”。中华神经影像学杂志35.5 (2025):e70085。在表7中,文本“dawm”是一个错字,应该删除。此外,该表应以两位有效数字表示所有值。我们为这个错误道歉。表7所示。在所有模型的临床数据集中进行2D和3D扫描的性能比较。注意:每个指标提供了五个主题的平均值。缩写:LFPR,病变假阳性率;LTPR:病变真阳性率;RVD,相对容积差。
Correction to “A Novel Convolutional Neural Network for Automated Multiple Sclerosis Brain Lesion Segmentation”
E Dereskewicz, F La Rosa, J Dos Santos Silva, et al. “A Novel Convolutional Neural Network for Automated Multiple Sclerosis Brain Lesion Segmentation.” Journal of Neuroimaging 35.5 (2025): e70085.
In Table 7, the text “dawm” was a typo and should have been removed. In addition, the table should present all values with two significant figures.
We apologize for this error.
Table 7. Performance comparison between 2D and 3D scans in the clinical dataset across all models.
Note: Average values across five subjects are provided for each metric.
期刊介绍:
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