In treating a patient with deviated nasal septum (DNS), a surgeon draws up a surgical plan based on the patient's rhinomanometry outcomes and self-assessment of nose conditions, e.g. the nasal obstruction septoplasty effectiveness (NOSE) score. However, the procedure fails to localize the DNS and determine the nose's aerodynamic effects. This paper proposes a DNS-aided surgery approach using computational fluid dynamics (CFD) and computed tomography (CT) techniques consisting of three main processes: preoperative, presurgical planning, and postoperative processes. The healthy baseline refers to a benchmark consisting of five subjects without DNS and nasal airway obstructions. To assess the possibility of using the CFD-CT-aided surgery approach as a presurgical planning tool in the DNS operation, comparative tests were carried out with DNS patient #1, who received a conventional nasal surgery without the proposed presurgical planning. Although DNS patient #1's surgical outcome was relatively satisfying to the patient, evaluating from the reduction of the NOSE score the conventional surgical method could induce an excessive excision of nasal airway, resulting in water loss in the nasal mucosa and a large reduction in airflow velocity. In addition, the postoperative nasal resistance measured by a rhinomanometer was not acceptable to the surgeon. Virtual surgery using the CFD-CT approach performed after surgery could suggest suitable patient-specific components of nasal operation with predictable results. Subsequently, implementation of the proposed CFD-CT approach in aid of DNS surgery was performed in DNS patient #2. The benefits of the CFD-CT-aided surgery approach were determined based on the pre-and postoperative outcomes (i.e. nasal geometric data and nasal airflow patterns), NOSE scores, and rhinomanometric data of DNS patient #2, which were compared against those of the healthy baseline benchmark. The CFD-CT approach could assist the surgeon to localize the DNS and determine the defective nasal tissues to be removed. The actual postoperative outcomes were clinically acceptable to the surgeon and DNS patient #2. It is evident that the CFD-CT-aided surgery approach is suitable for and applicable to surgery of DNS patients with small variability from the presurgical planning stage.

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A challenge of current research concerning eye motion estimation is to estimate motion of a three-dimensional (3D) eye model from a two-dimensional (2D) eye image. This paper proposed a new method to estimate rotation angle of 3D eye model from a 2D eye image by angular orientation identification technique. Real eye movement is captured from a camera mounting on a side of a binocular. A camera focuses on an eye. This method consists of three steps: 1) pupil extraction from a 2D image, 2) ellipse fitting technique, and 3) angular orientation identification. First, 3D eye model orients related real 2D eye image movement. Pupil is extracted to measure its shape in second step. Second, ellipse fitting technique is used to construct complete shape of pupil. Lengths of major and minor axis are computed from ellipse shape. Finally, angular orientation of 3D eye is estimated from major and minor axis length. Rotation angle is defined from lookup table of lengths of ellipse axis and rotation angle. To evaluate the estimation model, computational result will be compared with manual measurement. Rotation angle is varied from -50 degrees to +50 degrees in yaw and roll axis with step of three degrees. Precision of the mathematical model to simulate 3D eye model orientation in roll and yaw direction are 99.53% and 99.29%, respectively. The advantage of this method over other methods is that eye motion in 3D space can be estimated from only one camera.

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