Automatic Quantification of Radiographic Finger Joint Space Width of Patients With Early Rheumatoid Arthritis

作者：Huo Yinghe^*; Vincken Koen L; van der Heijde Desiree; De Hair Maria J H; Lafeber Floris P; Viergever Max A

来源：IEEE Transactions on Biomedical Engineering, 2016, 63(10): 2177-2186.

DOI：10.1109/TBME.2015.2512941

• Finger joint detection
• hand bone segmentation
• joint space width quantification
• rheumatoid arthritis

The assessment of joint space width (JSW) on hand X-ray images of patients suffering from rheumatoid arthritis (RA) is a time-consuming task. Manual assessment is semiquantitative and is observer dependent which hinders an accurate evaluation of joint damage, particularly in the early stages. Automated analysis of the JSW is an important step forward since it is observer independent and might improve the assessment sensitivity in the early RA stage. This study proposes a fully automatic method for both joint location and margin detection in RA hand radiographs. The location detection procedure is based on image features of the joint region and is aided by geometric relationship of finger joints. More than 99% of joint locations are detected with an error smaller than 3 mm with respect to the manually indicated gold standard. The joint margins are detected by combining intensity values and spatially constrained intensity derivatives, refined by an active contour model. More than 96% of the joints are successfully delineated. The JSW is calculated over the middle 60% of a landmark-defined joint span. The overall JSW error compared with the ground truth is 6.8%. In conclusion, the proposed method is able to automatically locate the finger joints in RA hand radiographs, and to quantify the JSW of these joints.

• 出版日期2016-10