Computational Methods and Clinical Applications in Musculoskeletal Imaging - 6th International Workshop, MSKI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers
Computational Methods and Clinical Applications in Musculoskeletal Imaging - 6th International Workshop, MSKI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers
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肌肉骨骼成像中的计算方法和临床应用 - 第六届国际研讨会，MSKI 2018，与 MICCAI 2018 联合举行，西班牙格拉纳达，2018 年 9 月 16 日，修订后的精选论文
DOI：
10.1007/978-3-030-11166-3_2
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Blanco N
中科院分区：
文献类型：
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作者：
Blanco N
这项工作解决了在全景牙齿图像中分割牙齿的问题。首先应用随机森林回归投票约束局部模型定位下颌骨和每颗牙齿的大致位置，然后定位每颗牙齿的完整轮廓。提出了一种自动计算的适合度来识别缺失的牙齿。该系统使用了346张包含成人期下颌牙齿的手动注释图像进行了评估。在检测牙齿缺失方面取得了令人鼓舞的结果。该系统在定位现有牙齿轮廓方面取得了最先进的性能，每颗牙齿的中位点到曲线误差为0.2 mm。
This work addresses the problem of segmenting teeth in panoramic dental images. Random forest regression voting constrained local models were applied firstly to locate the mandible and the approximate pose of each tooth, and secondly to locate the full outline of each individual tooth. An automatically computed quality-of-fit measure was proposed to identify missing teeth. The system was evaluated using 346 manually annotated images containing adult-stage mandibular teeth. Encouraging results were achieved for detecting missing teeth. The system achieved state-of-the-art performance in locating the outline of present teeth with a median point-to-curve error of 0.2 mm for each of the teeth.