(A) Schematic of the scan-to-prediction pipeline for
molecular subtype classification. The pipeline inputs the raw
T2-weighted (T2W) MRI scan and outputs the mutation class prediction.
(B) Input and output depiction of the segmentation
model from the first stage of the pipeline. The segmentation block also
involves registration and preprocessing of the input scan. The output
consists of the preprocessed input MRI scan along with the coregistered
segmentation mask. (C) Flow diagram of the TransferX
training block and approach. The TransferX algorithm is employed to
train three individual subtype classifiers (BRAF wild
type, BRAF fusion, and BRAF V600E).
(D) The model architecture of the individual binary
molecular subtype classifier. (E) Schematic of the
consensus decision block. The block inputs the classification outputs
and corresponding scores from the three individual subtype classifiers,
fits them into a consensus logic, and outputs the final predictions. The
mutational class predictions are output sequentially where the input is
first checked for BRAF wild type or
non-BRAF class first. If the input does not belong
to a BRAF wild type or non-BRAF class,
then the logic progresses to check the BRAF mutation
class, with BRAF fusion checked first, followed by
BRAF V600E.