Orthognathic Surgical planning based on Soft Computing Science including Self Organizing Map

基于包括自组织图在内的软计算科学的正颌手术规划

• 批准号: 13672181
• 负责人: MASUI Ichiro
• 金额: $ 1.6万
• 依托单位: Fukuoka College of Health Sciences
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2001
• 资助国家: 日本
• 起止时间: 2001 至 2003
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-13672181/
• 关键词: Jaw deformity; Classification of Profile; Planning of orthognathic surgery; Soft computing; Cephalogram; Prediction of postoperative profile; Application software; Graphical Database; 自己組織化マップ; 遺伝的アルゴリズム; ネオファジィニューロン; 側貌予測; 症型分類; 術後側貌予測; ユーザ

We developed an artificial intelligent system based on soft computing for planning of orthognathic surgery in surgical correction of jaw deformities.The self-organizing map neural network (SOM) has a feature of a mapping from a high dimensional space to a low dimensional space with keeping its topology. Accordingly, similar cases are closely located on the map. Using this feature, we applied SOM to classification of soft-tissue profiles of jaw deformities. Materials were pre-and post-operative lateral cephalograms of 44 patients. Soft-tissue profiles were measured and classified (diagnosed) into seven groups. Eleven soft-tissue measurements were selected as input vector of SOM. The genetic algorithm (GA) was employed to optimize coefficients for each measurement. The hierarchical classification method based SOM and GA resulted about 100% corresponding to the previous profile diagnosis.In planning of orthognathic surgery case, it is meaningful to refer the past documentation similar to the new case. We constructed database software that automatically searches for similar cases from a number of various cases stored by means of SOM. It is also useful to predict the profile after surgery. Profile change is a nonlinear result from the interaction of not only skeletal movement but also soft tissue thickness. Using neo fuzzy neuron that can approximate a nonlinear relationship between inputs and outputs. Comparing prediction errors between the neo frizzy neuron method and the linear multiple regression method, the neo fuzzy neuron method was suitable for prediction of resultant profile after orthognathic surgery. A photograph of the patient's predicted profile can be made from that before surgery using morphing technique.

开发了一种基于软计算的颌骨畸形矫正正颌外科手术规划的人工智能系统。自组织映射神经网络(SOM)具有从高维空间到低维空间的映射并保持其拓扑结构的特点。因此，类似的案例在地图上位置很近。利用这一特征，我们将SOM应用于颌骨畸形的软组织轮廓分类。材料为44例患者术前、术后头颅侧位片。测量软组织侧貌并将其分类(诊断)为7组。选取11个软组织测量值作为SOM的输入向量。采用遗传算法(GA)对每个测量值的系数进行优化。基于SOM和GA的层次分类方法与以往的轮廓诊断结果吻合100%，在正颌外科病例的规划中，参考与新病例相似的以往文献具有一定的意义。我们构建了一个数据库软件，可以从通过SOM存储的大量不同的案例中自动搜索相似的案例。预测手术后的情况也是有用的。侧貌变化是骨骼运动和软组织厚度相互作用的非线性结果。使用新的模糊神经元，它可以逼近输入和输出之间的非线性关系。比较新模糊神经元法和线性多元回归法的预测误差，新模糊神经元法更适合于正颌外科手术后外形的预测。使用变形技术，可以从手术前的照片中制作出患者预测的轮廓照片。

项目成果

堀尾恵一, 升井一朗, 山川 烈: "症型分類に基づいた顎変形症術後側貌の予測"バイオメディカル・ファジィ・システム学会第15回年次大会講演予稿集. 1・1. 21-24 (2002)

Keiichi Horio、Ichiro Masui、Retsu Yamakawa：“基于疾病类型分类的颌畸形手术后的外观预测”第 15 届生物医学模糊系统学会年会记录 1・1（2002 年）。

山川 烈, 升井一朗, 堀尾恵一, 熊本将志: "重み付き距離測度を用いた階層型自己組織化マップによる分類手法"第3回自己組織化マップ研究会予稿集. 1・1. 39-42 (2001)

Retsu Yamakawa、Ichiro Masui、Keiichi Horio、Masashi Kumamoto：“使用加权距离度量的分层自组织映射的分类方法”第 3 届自组织映射研究小组论文集 1・1（2001 年）。

Keiichi Horio, Ichiro Masui, Masashi Kumamoto, Takeshi Yamakawa: "PREDICTION OF RESULTANT PROFILE AFTER ORTHOGNATHIC SURGERY BASED ON CLASSIFICATION OF PROFILE BEFORE SURGERY"Proceedings of the 15th Annual Meeting of Biomedical Fuzzy Systems Association.

Keiichi Horio、Ichiro Masui、Masashi Kumamoto、Takeshi Yamakawa：“基于手术前轮廓分类的正畸手术后结果轮廓的预测”生物医学模糊系统协会第 15 届年会论文集。

K.Horio, I.Masui, M.Kumamoto, T.Yamakawa: "Hierarchical Classification Method Based on Self-Organizing Maps and Genetic Algorithm"Proc.of the 1st Int.Conf.on Soft Computing and Inteligent Systems(SCIS2002). in CD-ROM. (2002)

K.Horio，I.Masui，M.Kumamoto，T.Yamakawa：“基于自组织映射和遗传算法的层次分类方法”Proc.of the 1st.Conf.on SoftComputing and Inteligent Systems(SCIS2002)。

K.Horio, I.Masui, M.Kumamoto, T.Yamakawa: "Hierarchical Classification Method Based On Self-Organizing Maps And Genetic Algorithm"Proc.of the 1st Int.Conf.on Soft Computing and Intelligent Systems (SCIS2002). CD-ROM. (2002)

K.Horio、I.Masui、M.Kumamoto、T.Yamakawa：“基于自组织映射和遗传算法的层次分类方法”Proc.of the 1st Int.Conf.on Soft Computing and Intelligence Systems (SCIS2002)。