چکیده (انگلیسی):

Detection and segmentation of fissures is useful in the clinical interpretation of CT lung images to diagnose
the presence of pathologies in the human lungs. A new automated method based on marker-based watershed
transformation has been proposed to segment the fissures considering its unique structure as a long
connected component. Marker based watershed transformation is applied and morphological operations
are employed to specify the internal and external markers. The smaller regions in the resulting image
are removed by a novel procedure called Small Segment Removal Algorithm (SSRA) to segment the
fissures alone. The performance of the method is validated by experimenting with 6 CT image sets. An
expert radiologist observation is used as reference to assess the performance. A promising accuracy of
96.61% is shown with the rms error in the range of 0.877±0.224 mm for the left oblique fissure and
0.803±0.262 mm for the right oblique fissure.