ACPC transform question


I have been trying to figure out how to transform a scan so that it aligns to the ACPC plane. I’ve tried using this module ( and placing fiducial points on different slices to transform the scan, but have been unsuccessful. Can anyone explain how I can do this? Also, is there a way to overlay a grid on the scan or in some way calculate just horizontal distance with the ruler?

Thank you!

Hi Alexis,

You can try this code on the Python console:

import numpy as np
import SampleData

def getSampleVolume():
    # Download MRHead
    sampleDataLogic = SampleData.SampleDataLogic()
    volumeNode = sampleDataLogic.downloadMRHead()
    return volumeNode

def getMatrixToACPC(ac, pc, ih):
    # Anteroposterior axis
    pcAc = ac - pc
    yAxis = pcAc / np.linalg.norm(pcAc)
    # Lateral axis
    acIhDir = ih - ac
    xAxis = np.cross(yAxis, acIhDir)
    xAxis /= np.linalg.norm(xAxis)
    # Rostrocaudal axis
    zAxis = np.cross(xAxis, yAxis)
    # Rotation matrix
    rotation = np.vstack([xAxis, yAxis, zAxis])
    # AC in rotated space
    translation =, ac)
    # Build homogeneous matrix
    matrix = np.eye(4)
    matrix[:3, :3] = rotation
    matrix[:3, 3] = translation
    return matrix

def getTransformNodeFromNumpyMatrix(matrix, name=None):
    # Create VTK matrix object
    vtkMatrix = vtk.vtkMatrix4x4()
    for row in range(4):
        for col in range(4):
            vtkMatrix.SetElement(row, col, matrix[row, col])
    # Create MRML transform node
    transformNode = slicer.mrmlScene.AddNewNodeByClass(
    if name is not None:
    return transformNode

# I defined these on MRHead
ac = np.array([-0.0641399910762672, 17.61291529545006, 5.009494772024041])
pc = np.array([-0.5843405105866637, -10.4779127581112, 3.044020167647495])
ih = np.array([-1.1045410300970602, 1.746799450383008, 45.04402016764749])

volumeNode = getSampleVolume()
matrix = getMatrixToACPC(ac, pc, ih)
transformNode = getTransformNodeFromNumpyMatrix(matrix, name='World to ACPC')

# Create markups node with AC, PC and an interhemispheric point
markupsNode = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLMarkupsFiducialNode')
markupsNode.AddFiducialFromArray(ac, 'AC')
markupsNode.AddFiducialFromArray(pc, 'PC')
markupsNode.AddFiducialFromArray(ih, 'IH')

# Apply transform to volume node and markups node

# Fit image to slices
applicationLogic =

# Center views on AC
markupsLogic = slicer.modules.markups.logic()
acIndex = 0
markupsLogic.JumpSlicesToNthPointInMarkup(markupsNode.GetID(), acIndex)

By the way, looking forward to showing examples like these in a Jupyter Notebook :slight_smile:

These may help (they are accurate for Slicer 3.6, but the behavior is not that much different on Slicer 4.9):

If you still have problems, then please describe what you did exactly, what you expected to happen, and what happened instead.