# A Linkage Representation of the Human Hand Skeletal System Using CT Hand Scan Images
## 2 Materials and Methods
### CT Data Acquisition and Processing  
CT data of the right hand of each participant in ten postures were acquired by a radiologist at Pohang Stroke and Spine Hospital. As shown in Figure 1, the ten postures were sequentially selected from a natural hand motion starting from a fully extended posture (Posture 1) and ending at a fist posture (Posture 10) with an approximately 10-degree difference in flexion of the PIP joint of the index finger between two adjacent postures visually estimated by an experimenter. The difference was not objectively measured during the CT scan to guarantee natural motions of the hand. A 256-slice CT scanner (Brilliance iCT; Philips Healthcare, Cleveland, OH, USA) was used to sequentially scan the ten postures while a participant was steadily holding each of the ten postures. The dorsal hand of a participant lay on a device individually fabricated by paper clay for each participant to fix the hand of the participant. The scanning was performed within one minute to capture the ten postures (3 to 5 s per scan) for each participant. The participants were covered by a lead-free radiation shielding apron (FC001; Longkou Sanyi Medical Device Co., Ltd., Longkou, China) and asked to lie face down and stretch out their right arms over their heads to keep the rest of their body away from the CT scanner to protect them from radiation during scanning. Each scan consisted of 576 to 670 CT slices with a resolution of 512 \(\times\) 512 pixels and a slice thickness of 0.44 mm for a posture depending on the participant's hand size. More detailed information on the CT data acquisition method can be found in our previous paper [15].  
The 3D skin and skeleton of a participant's hand in each of the ten postures were semiautomatically reconstructed from the corresponding CT data by the Medical Imaging Interaction Toolkit (MITK) [16]. The connected twenty-nine bone segments, including the radius, ulna, eight carpal bones (hamate, pisiform, triquetral, lunate, scaphoid, capitate, trapezium, and trapezoid), five metacarpals, five proximal phalanges, four middle phalanges, and five distal phalanges, in Posture 1 were manually separated by a subtraction function in MITK. Each of the separated bone segments was exported as a file with the polygon (PLY) format by RapidForm 2006 (Inus Technology, Inc., Seoul, Korea). The twenty-nine bone segments in Posture 1 (template posture) were then registered to those in the remaining nine postures so that all the bone segments in the ten postures had the same bone surfaces. First, each bone in Posture 1 was roughly registered to that in a target posture by aligning three points selected at a similar position, each from the template bone surface and the target bone surface. Then, a fine registration was performed to precisely register the template bone to the target bone using the iterative closest point (ICP) algorithm [17]. More detailed information on the registration method can be found in our previous paper [15].  
Figure 1: Ten postures from a natural hand-closing motion starting from a fully extended posture (Posture 1) and ending at a fist posture (Posture 10) to estimate hand joint centers, adopted from our previous paper [15].