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- registration getting better

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This commit is contained in:
Wim Pomp
2026-07-29 21:48:02 +02:00
parent bb3d46cc9d
commit 001df705ef
3 changed files with 52 additions and 35 deletions
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src/metric.rs
+4 -4
View File
@@ -212,7 +212,7 @@ where
shape: Vec<f64>,
center: Vec<f64>,
fixed: BSpline<0, D>,
moving: BSpline<1, D>,
moving: BSpline<3, D>,
fixed_mu: FixedMu,
minmax: [f64; 2],
sampling: Sampling,
@@ -230,7 +230,7 @@ where
{
pub fn new(
fixed: BSpline<0, D>,
moving: BSpline<1, D>,
moving: BSpline<3, D>,
sampling: SamplingArg,
n_bins: usize,
edge: f64,
@@ -776,7 +776,7 @@ mod tests {
let a = array![0.0, 0.0, 1.0, 0.0, 1.0, 2.0, 1.0, 0.0, 1.0, 0.0, 0.0];
let b = array![0.0, 0.0, 1.0, 0.0, 1.0, 2.0, 1.0, 0.0, 1.0, 0.0, 0.0];
let fixed = BSpline::<0, _>::new(a.view());
let moving = BSpline::<1, _>::new(b.view());
let moving = BSpline::<3, _>::new(b.view());
let mus = vec![0.0, 0.001];
let mut npz = NpzWriter::new(File::create(
@@ -857,7 +857,7 @@ mod tests {
let a = array![0.0, 0.0, 1.0, 0.0, 1.0, 2.0, 1.0, 0.0, 1.0, 0.0, 0.0];
let b = array![0.0, 0.0, 1.0, 0.0, 1.0, 2.0, 1.0, 0.0, 1.0, 0.0, 0.0];
let fixed = BSpline::<0, _>::new(a.view());
let moving = BSpline::<1, _>::new(b.view());
let moving = BSpline::<3, _>::new(b.view());
let mus = Array1::linspace(-10.0, 10.0, 500);
let s = a.len() as f64;
src/register.rs
+18 -14
View File
@@ -19,7 +19,7 @@ pub enum Optimizer {
impl Default for Optimizer {
fn default() -> Self {
Self::ASGD
Self::LBFGS
}
}
@@ -61,16 +61,16 @@ impl RegistrationStep {
///
/// Uses a multi-resolution pyramid with downsampling matching SimpleElastix:
/// schedule [8, 4, 2, 1] → σ = [4.0, 2.0, 1.0, 0.5] at spacing=1.
/// 512 iterations per level, 2048–8192 cached random samples.
/// Uses all pixels at all levels for deterministic, precise convergence.
pub fn default_steps(ndim: usize, n: usize) -> Vec<Self> {
if ndim == 1 {
return vec![Self {
sigma: Sigma::Absolute(vec![1.0; 1]),
samples: SamplingArg::Random(2048.min(n)),
samples: SamplingArg::Random(n),
n_bins: 32,
tolerance: 1e-6,
tolerance: 1e-8,
edge: 0.05,
max_iterations: 1500,
max_iterations: 2048,
learning_rate: 1.0,
downsample: 1,
}];
@@ -78,19 +78,23 @@ impl RegistrationStep {
// Pyramid with downsampling: schedule [8,4,2,1], sigma [4,2,1,0.5]
let sigma_schedule: Vec<f64> = vec![4.0, 2.0, 1.0, 0.5];
let downsample_schedule: Vec<usize> = vec![8, 4, 2, 1];
let n_levels = sigma_schedule.len();
sigma_schedule
.iter()
.zip(downsample_schedule.iter())
.map(|(&s, &d)| {
.enumerate()
.map(|(level, (&s, &d))| {
let n_pixels = (n / (d * d)).max(4);
let n_samples = n_pixels.min(8192).max(2048);
let is_finest = level == n_levels - 1;
// Use all pixels at all levels for deterministic results
let (max_iter, tol) = if is_finest { (2048, 1e-8) } else { (512, 1e-6) };
Self {
sigma: Sigma::Absolute(vec![s; ndim]),
samples: SamplingArg::Random(n_samples),
samples: SamplingArg::Random(n_pixels),
n_bins: 32,
tolerance: 1e-6,
tolerance: tol,
edge: 0.05,
max_iterations: 512,
max_iterations: max_iter,
learning_rate: 1.0,
downsample: d,
}
@@ -318,7 +322,7 @@ impl<D: Dimension> Registration<D> {
continue;
}
let bf = BSpline::<0, _>::new(f.view());
let bm = BSpline::<1, _>::new(m.view());
let bm = BSpline::<3, _>::new(m.view());
let metric = MattesMetric::new(bf, bm, samples, n_bins, edge)?
.with_fixed_mu(self.fixed_mu.clone());
@@ -344,7 +348,7 @@ impl<D: Dimension> Registration<D> {
tolerance,
maximum_step_length: 1.0,
sp_a: 20.0,
sp_alpha: 1.0,
sp_alpha: 0.602,
scales: Some(scales),
..Default::default()
};
@@ -418,7 +422,7 @@ impl<D: Dimension> Registration<D> {
}
let bf = BSpline::<0, _>::new(f.view());
let bm = BSpline::<1, _>::new(m.view());
let bm = BSpline::<3, _>::new(m.view());
let n_samples = match &samples {
SamplingArg::Fixed(n) => *n,
SamplingArg::Random(n) => *n,
@@ -449,7 +453,7 @@ impl<D: Dimension> Registration<D> {
tolerance,
maximum_step_length: 1.0,
sp_a: 20.0,
sp_alpha: 1.0,
sp_alpha: 0.602,
scales: Some(scales),
..Default::default()
};
src/transform.rs
+30 -17
View File
@@ -749,7 +749,7 @@ mod tests {
)
.slice(s![.., 0])
.mapv(|i| i as f64);
let q = vec![0.85, 4.0];
let q = vec![0.85, 2.0];
let im_b =
Transform::new(q.clone(), vec![im_a.shape()[0]]).interpolate::<1, _, _>(&im_a)?;
@@ -871,7 +871,7 @@ mod tests {
let f = gaussian_smooth(im_a.view(), &[*sigma_val; 2])?;
let m = gaussian_smooth(im_b.view(), &[*sigma_val; 2])?;
let bf = BSpline::<0, _>::new(f.view());
let bm = BSpline::<1, _>::new(m.view());
let bm = BSpline::<3, _>::new(m.view());
let metric = MattesMetric::new(bf, bm, SamplingArg::Random(3000), 128, edge)?;
let mi_id = metric.evaluate(&identity);
@@ -899,7 +899,7 @@ mod tests {
let f4 = gaussian_smooth(im_a.view(), &[4.0, 4.0])?;
let m4 = gaussian_smooth(im_b.view(), &[4.0, 4.0])?;
let bf4 = BSpline::<0, _>::new(f4.view());
let bm4 = BSpline::<1, _>::new(m4.view());
let bm4 = BSpline::<3, _>::new(m4.view());
let metric4 = MattesMetric::new(bf4, bm4, SamplingArg::Random(5000), 128, edge)?;
let mi_p_coarse = metric4.evaluate(&p);
let mi_qinv_coarse = metric4.evaluate(&q_inv);
@@ -943,7 +943,7 @@ mod tests {
let m = gaussian_smooth(im_b.view(), &[4.0, 4.0])?;
let metric = MattesMetric::new(
BSpline::<0, _>::new(f.view()),
BSpline::<1, _>::new(m.view()),
BSpline::<3, _>::new(m.view()),
SamplingArg::Random(3000),
128,
edge,
@@ -1022,13 +1022,24 @@ mod tests {
.fold(0.0f64, f64::max);
println!("Our: {:?} max_err: {:.4} sse: {:.4}", t, max_err, sse);
let mut tif = IJTiffFile::new(std::env::home_dir().unwrap().join("tmp/register_real_images.tif"))?;
let mut tif = IJTiffFile::new(
std::env::home_dir()
.unwrap()
.join("tmp/register_real_images.tif"),
)?;
tif.save(fixed.mapv(|i| i as u16), 0, 0, 0)?;
tif.save(t.interpolate_par::<1, _, _>(moving.view())?.mapv(|i| i as u16), 1, 0, 0)?;
tif.save(
t.interpolate_par::<1, _, _>(moving.view())?
.mapv(|i| i as u16),
1,
0,
0,
)?;
tif.save(moving.mapv(|i| i as u16), 2, 0, 0)?;
assert!(max_err < 0.1);
assert!(sse < 0.1);
assert!(max_err < 0.02);
assert!(sse < 0.02);
Ok(())
}
@@ -1036,7 +1047,8 @@ mod tests {
#[test]
fn register_real_images2() -> Result<(), Box<dyn std::error::Error>> {
let fixed = read_tiff("test_files/fixed.tif")?;
let e = Transform::<Ix2>::new(vec![0.8, 0.0, 0.0, 1.0, 0.0, 0.0], fixed.shape().to_vec()).inverse()?;
let e = Transform::<Ix2>::new(vec![0.8, 0.0, 0.0, 1.0, 0.0, 0.0], fixed.shape().to_vec())
.inverse()?;
let moving = e.interpolate::<3, _, _>(fixed.view())?;
let t = Transform::<Ix2>::register(
@@ -1047,27 +1059,28 @@ mod tests {
None,
)?;
let e_inv = e.inverse()?;
let sse = t
.parameters
.iter()
.zip(e.parameters.iter())
.zip(e_inv.parameters.iter())
.map(|(a, b)| (a - b).powi(2))
.sum::<f64>();
let max_err = t
.parameters
.iter()
.zip(e.parameters.iter())
.zip(e_inv.parameters.iter())
.map(|(a, b)| (a - b).abs())
.fold(0.0f64, f64::max);
println!("Our: {:?} max_err: {:.4} sse: {:.4}", t, max_err, sse);
// let mut tif = IJTiffFile::new(std::env::home_dir().unwrap().join("tmp/register_real_images2.tif"))?;
// tif.save(fixed.mapv(|i| i as u16), 0, 0, 0)?;
// tif.save(t.interpolate_par::<1, _, _>(moving.view())?.mapv(|i| i as u16), 1, 0, 0)?;
// tif.save(moving.mapv(|i| i as u16), 2, 0, 0)?;
let mut tif = IJTiffFile::new(std::env::home_dir().unwrap().join("tmp/register_real_images2.tif"))?;
tif.save(fixed.mapv(|i| i as u16), 0, 0, 0)?;
tif.save(t.interpolate_par::<1, _, _>(moving.view())?.mapv(|i| i as u16), 1, 0, 0)?;
tif.save(moving.mapv(|i| i as u16), 2, 0, 0)?;
assert!(max_err < 0.1);
assert!(sse < 0.1);
assert!(max_err < 0.02);
assert!(sse < 0.02);
Ok(())
}