Shehtab Zaman

Medical and astronomical images are orders of magnitude larger than natural images, yet tumors and galaxies occupy a tiny fraction of the data, and uniform compression such as quantization or pruning can erode precision exactly there. Conformal Adaptation first screens candidates with a low-resolution model, calibrates the selection threshold with conformal risk control so the discarded cells carry at most a user-set expected fraction of true signal mass, then refines only the selected regions. Across brain-tumor segmentation, head-and-neck segmentation, calcium spike-rate inference and galaxy flux super-resolution, the pipeline cuts computation while keeping accuracy close, and VISTA3D reaches an 82.10x FLOPs speedup in CPU-only inference.

Medical and astronomical images are orders of magnitude larger than natural images, yet tumors and galaxies occupy a tiny fraction of the data, and uniform compression such as quantization or pruning can erode precision exactly there. Conformal Adaptation first screens candidates with a low-resolution model, calibrates the selection threshold with conformal risk control so the discarded cells carry at most a user-set expected fraction of true signal mass, then refines only the selected regions. Across brain-tumor segmentation, head-and-neck segmentation, calcium spike-rate inference and galaxy flux super-resolution, the pipeline cuts computation while keeping accuracy close, and VISTA3D reaches an 82.10x FLOPs speedup in CPU-only inference.