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Pathologic myopia (PM) is a common blinding retinal degeneration suffered by
highly myopic population. Early screening of this condition can reduce the
damage caused by the associated fundus lesions and therefore prevent vision
loss. Automated diagnostic tools based on artificial intelligence methods can
benefit this process by aiding clinicians to identify disease signs or to
screen mass populations using color fundus photographs as inputs. This paper
provides insights about PALM, our open fundus imaging dataset for pathological
myopia recognition and anatomical structure annotation. Our databases comprises
1200 images with associated labels for the pathologic myopia category and
manual annotations of the optic disc, the position of the fovea and
delineations of lesions such as patchy retinal atrophy (including peripapillary
atrophy) and retinal detachment. In addition, this paper elaborates on other
details such as the labeling process used to construct the database, the
quality and characteristics of the samples and provides other relevant usage
notes.
