Perf: skip redundant full-image mask on StdShiftIntensity nonzero=False path

[aymuos15]

Fixes #8972 .

Description

On the default nonzero=False path StdShiftIntensity._stdshift built an all-True boolean mask the size of the image and shifted through it (img[slices] = img[slices] + offset), forcing a full advanced-index gather and scatter plus the mask allocation and .any() scan even though every voxel is selected. That is equivalent to shifting the image directly, so the nonzero=False branch now does img + factor * std(img). Output is bit-for-bit identical and the nonzero=True path is untouched. RandStdShiftIntensity benefits too, since it also defaults to nonzero=False. Measured across 2D/3D, single and multi channel, float32 and float64 on both backends (best-of-3, CPU); output verified equal in every configuration:

shape	dtype	backend	current (ms)	proposed (ms)	speedup
1x256x256	f32	numpy	0.123	0.048	2.58x
1x256x256	f32	torch	0.563	0.039	14.47x
1x1024x1024	f32	numpy	3.016	1.294	2.33x
1x1024x1024	f32	torch	7.040	0.274	25.66x
1x1024x1024	f64	torch	9.644	0.601	16.04x
1x64x64x64	f32	numpy	0.637	0.251	2.54x
1x64x64x64	f64	torch	2.646	0.095	27.84x
1x128x128x128	f32	numpy	7.019	2.914	2.41x
1x128x128x128	f32	torch	41.618	0.630	66.09x
1x128x128x128	f64	torch	44.534	1.825	24.40x
4x96x96x96	f32	torch	68.152	1.357	50.23x
4x160x160x160	f32	numpy	128.429	82.662	1.55x
4x160x160x160	f32	torch	342.641	16.727	20.48x
4x160x160x160	f64	torch	354.009	41.652	8.50x

numpy ranges 1.55x to 2.65x and torch 8.5x to 66x across the full sweep; the largest gains are on torch, where all-True boolean-mask indexing is especially costly.

Types of changes

• Non-breaking change (fix or new feature that would not break existing functionality).

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📥 Commits

Reviewing files that changed from the base of the PR and between f72c648 and 2e4fafe.

📒 Files selected for processing (1)

• monai/transforms/intensity/array.py

🚧 Files skipped from review as they are similar to previous changes (1)

• monai/transforms/intensity/array.py

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📝 Walkthrough

Walkthrough

StdShiftIntensity._stdshift now computes std(img) directly on the default nonzero=False path and returns img + factor * std(img). The nonzero=True path still builds slices = img != 0, checks for any nonzero elements, and applies the shift to img[slices] in place.

File	Change Summary
monai/transforms/intensity/array.py	Simplified _stdshift for the default full-image path; kept masked behavior for nonzero inputs.

Estimated code review effort: 1 (Trivial) | ~3 minutes

Related issues: #8972

Suggested labels: performance, transforms

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly summarizes the performance optimization to StdShiftIntensity on the nonzero=False path.
Description check	✅ Passed	The description matches the template well, includes the fix, a change summary, and the non-breaking change type.
Linked Issues check	✅ Passed	The code change matches #8972 by removing the redundant full-image mask path while leaving nonzero=True behavior intact.
Out of Scope Changes check	✅ Passed	The PR appears scoped to the requested StdShiftIntensity optimization and adds no unrelated changes.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.

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