F.A.Q.¶

This page contains the answers to Frequently Asked Question(s) (F.A.Q.) and will be gradually populated.

General Questions¶

Q1:   Is the direction information stored in the NIfTI files physically accurate? I have observed that all images in the dataset are in the 'RAI' direction. Will there be images with a different direction in the Final Test Phase? If so, will the direction information be stored accurately in the file metadata?

A1: Yes, the metadata is physically accurate and will also be so in the test set. Anyway, all images selected for the Final Test Phase will have RAI direction.

Task 1: Fast Multi-class Segmentation¶

Q1: Data starting with "P" seems to be missing information related to the upper part of the oral cavity, including the upper teeth, maxilla, maxillary sinus, etc. Could you please confirm if this is indeed the case for the dataset?

A2: Yes, that is correct: handling such a different view is part of the challenge.  The training dataset can be divided into "Set A" (samples that begin with the letter "P"), "Set B" (samples that begin with the letter "F"), and "Set C" (samples that begin with the letter "S"). The acquisition machine for "Set A" and "Set B" is the same, while it differs for "Set C". The field of view of "Set C" is between that of the other two. For more details, please refer to Ditto. Test data are assured to have the same field of view as "F" cases.

Q2: As mentioned on the dataset homepage, the "Dataset classes" are listed as 77. However, in the dataset.json file, I find a total of more than 100 classes.

A2: Classes are 77, as specified on our webpage. Numbering in the dataset.json file goes up to 148, but if you look at the classes, you'll see that many of them are empty. This choice is to keep the teeth identifiers aligned with the standard FDI medical notation. Pulp cavities have the class ID of the corresponding teeth +100. Submitted algorithms should predict 77 classes only. 

Task 2: IAC Interactive Segmentation¶

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