Takamasa Sugiura1, Shuhei Nitta1, Taichiro Shiodera1, Yuko Hara1, Yasunori Taguchi1, Tomoyuki Takeguchi1, Takuya Fujimaki2, Kensuke Shinoda2, Hiroshi Takai2, and Ayako Ninomiya2
We propose an improved automatic slice positioning
algorithm for knee MR which combines conventional machine-learning based
landmark detection with advanced image processing techniques. Conventional slice
positioning methods determine the diagnostic slice center and orientation by detecting
anatomical landmarks in the scout image. However, computing slice positions
from landmarks can be inadequate since landmarks vary across patients and can
be cut-off from scout images. Here, we use not only landmark detection but also
image processing based contour detection of the femoral condyle and angle
estimation of the femur and tibia to enable slice positioning for a wider range
of scout images.
