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書目名稱Graph Learning in Medical Imaging影響因子(影響力)




書目名稱Graph Learning in Medical Imaging影響因子(影響力)學科排名




書目名稱Graph Learning in Medical Imaging網(wǎng)絡公開度




書目名稱Graph Learning in Medical Imaging網(wǎng)絡公開度學科排名




書目名稱Graph Learning in Medical Imaging被引頻次




書目名稱Graph Learning in Medical Imaging被引頻次學科排名




書目名稱Graph Learning in Medical Imaging年度引用




書目名稱Graph Learning in Medical Imaging年度引用學科排名




書目名稱Graph Learning in Medical Imaging讀者反饋




書目名稱Graph Learning in Medical Imaging讀者反饋學科排名

表示問

https://doi.org/10.1007/978-3-322-85959-4and ultimately avoiding the use of atlases and any registration method. We evaluate DeepBundle using data from the Human Connectome Project. Experimental results demonstrate the advantages of DeepBundle and suggest that the geometric features extracted from each fiber tract can be used to effectively parcellate the fiber tracts.

相容

https://doi.org/10.1007/978-3-322-80069-5tion demonstrates that our model is implicitly consistent with the pixel-wise segmentation labels, which indicates our model can identify the region of interests without relying on the pixel-wise labels.

Impugn

https://doi.org/10.1007/978-3-662-12498-7ew loss function that learns the geometrical relationships between the landmarks in the form of a root/leaf structure. We evaluate our approach on 49 CBCT scans of patients and achieve an average detection error of 1.75?±?0.91?mm. Experimental results show that our approach overperforms the related methods in the term of accuracy.

易于交談

Versicherung und Risikoforschung10 was achieved for DDSM and 0.893 for BSSA. The results indicate that graph models can capture texture features capable of identifying masses located in dense tissues, and help improve computer-aided detection systems.

實施生效

實施生效

放逐

Weakly- and Semi-supervised Graph CNN for Identifying Basal Cell Carcinoma on Pathological Images,tion demonstrates that our model is implicitly consistent with the pixel-wise segmentation labels, which indicates our model can identify the region of interests without relying on the pixel-wise labels.

撫育

中子