Feat Request: Conformal prediction

Is your feature request related to a problem? Please describe.

I want to be able to give a prediction set with a coverage guarantee beyond the current calibration and TTA.

Describe the solution you'd like
-- Collect softmax on a held out calibration, compute non conformity scores (LAC:1-softmax), take the empirical quintile as threshold and at inference return score(y) <= threshold.
-- Then calibrate a single threshold that bounds an image level loss, put a per voxel uncertainty mask

Potentially:
inferers/conformal_predictor.py
metrics/conformal_risk.py

Describe alternatives you've considered
External libraries like TorchCP

Additional context
https://arxiv.org/pdf/2208.02814

Start by reading the linked conformal prediction paper and reviewing the proposed inferers/conformal_predictor.py and metrics/conformal_risk.py entry points alongside MONAI's existing calibration and TTA behavior. The work is complete when calibrated prediction sets and the requested image-level or per-voxel uncertainty behavior are defined and integrated with verifiable coverage guarantees.