Continuous improvement of lungs segmentation algorithm #138
The initial lungs segmentation method has been provided by the PR #133 due to the issue #120. The provided approach, however, can be further improved e.g., by reducing its trend to false positives and made the algorithm more stable. Furthermore, the ability to correctly separate the tissues such as bones, lungs, bronchial, etc. will be beneficial for a further work with data augmentation.
For example, the work of van Rikxoort et al. describes the automatic error detection method via the convex hull complement to a coastline of lungs:
Furthermore, the method provided by S. Hu et al. is aimed at junction line enhancement followed by lungs separation which I've found to be unreasonable resource consumptive though.
The ability of the bronchial / lungs separation described in the paper of T. Kitasaka et al. I guess will also be valuable as an additional instrument of data augmentation.
P.S. Of course, contributions like a radiologist's handcrafted annotations of anatomical structures inside CT volume will be appreciated.
The lungs segmentation lied in the
The good measure of a lungs segmentation algorithm should be Hausdorff distance which has efficient implementation by
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Yep, we're definitely supposed to refine the lung segmentation. Have a look at e.g. patient 0001 and the nodule at 315.04852321, 365.87447257, -116.12078059 (slice ~91):