Automatic cochlear multimodal 3D image segmentation and analysis using atlas–model-based method

Figures & data

Figure 1 Top left: Cochlea and cochlear implant components. Top right: Fused cochlea image from CBCT, CT, and MR images. Bottom: Cochlear image segmentation of μCT showing the cochlea main scalae. Scala tympani in green and both scala vestibuli and scala media in red (top: 3D view: bottom from left to right: axial, sagittal, and coronal views).

Figure 2 Top: Image registration basic components. Bottom: Atlas–model-based concept.

Figure 3 Cochlea A-value method. The green points (x, y) are the A-value end points, the green line shows the A-value length.

Table 1 Datasets, images used in both experiments: 108

	Automatic experiments			Manual experiments
	G	E	Total	G	E	Total
Patients	41	26	67	34	26	60
Images	168	49	217	66	46	112
CBCT	75	23	98	57	18	75
CT	18	26	44	9	28	37
MR	75	0	38	0	0	0
Left	80	24	104	33	22	55
Right	88	25	113	33	24	57
Before surgery	125	25	104	34	25	59
After surgery	43	24	67	32	21	53

Figure 4 Top left: Cochlea landmarks in brown colour and A-value endpoints in yellow colour. Top right: The point models of scala tympani (in yellow) and scala vestibuli (in blue) central lengths. Bottom: The point models of scala tympani, the outer points in dark green colour for measuring the lateral wall length and the inner points in dark red for measuring the organ of corti length.

Figure 5 Cochlear segmentation using the new proposed high-resolution atlas in comparison to the low-resolution atlas proposed in ACA (Al-Dhamari et al. 2018).

Algorithm 1. ACA-v2

Input: Multimodal 3D clinical cochlea image I(P)

Output: Cochlear segmentation and different measurements

1: Locate the cochlea locations in input images

2: Crop the cochlea part into a smaller image: $\tilde{I}(P)$= Crop($I(P)$)

3: Apply ACIR-v3 on the cropped input image and the predefined image:

4:    $I_{\mathrm{res},T}=(\tilde{I}(P),I_M(P))$

5: Register the resulted image with the model image using B-spline transform:

6:   T= register $({\tilde{I}}_{\mathrm{res}0},I_M(P))$

7: Transform the segmentation and the point models:

8:   $I_{\mathrm{seg}}(P)=I_{M_{\mathrm{seg}}}(T(P),\mu )$, $I_{\mathrm{points}}(P)=I_{M_{\mathrm{points}}}(T(P),\mu )$

9: Output the segmentation and cochlea the measurements

Figure 6 Sample of the results from different image types with RMSE values. In each group, the image on the left has the lowest RMSE value and the image on the right has the highest RMSE value. Each result has the 3D model at the top and the three standard views at the bottom, i.e. axial, sagittal, and coronal.

Figure 7 Sample from the results: RMSE and time charts of different image groups. CBCT after and before surgery, CT, and MR.

Figure 8 Sample from the results: In-Patient-Error in mm. The comparison between automatic A-value method and manual A-value method (Lt and Oc are short for lateral wall and organ of corti).

Table 2 ACA-v2 measurements with IPE

	Scala vestibuli volume (mm${}^3$)	Scala tympani volume (mm${}^3$)	Scala vestibuli centre length (mm)	Scala tympani centre length (mm)
Mean	41.69	48.57	35.95	30.06
Std	2.0	2.24	0.53	0.45
Min	34.98	38.98	35.21	29.53
Max	49.3	57.67	38.79	32.21
IPE mean	1.79	1.91	0.61	0.52
IPE STD	1.26	1.3	0.47	0.4

Table 3 Scala tympani length measurements with their In-Patient-Error (IPE)

Length (mm)	A-value		Scala tympani lateral wall			Scala tympani organ-of-corti
Method	ACA-v2	Manual	ACA-v2	A-value auto.	A-value manual	ACA-v2	A-value auto.	A-value manual
Mean	8.96	9.02	43.88	39.58	39.82	31.77	32.23	32.49
STD	0.17	0.45	0.74	0.67	1.72	0.54	0.72	1.86
Min	8.75	8.21	42.93	38.75	36.69	31.11	31.34	29.12
Max	9.57	10.06	47.19	41.92	45.91	34.08	34.75	39.05
IPE mean	0.17	0.14	0.73	0.67	0.54	0.53	0.72	0.58
IPE STD	0.13	0.11	0.57	0.48	0.42	0.41	0.52	0.45

Al-Dhamari, I., Bauer, S., Paulus, D., Helal, R., Lisseck, F., Jacob, R. 2018. Automatic cochlear length and volume size estimation. In Or 2.0 context-aware operating theaters, computer assisted robotic endoscopy, clinical image-based procedures, and skin image analysis. Cham: Springer International Publishing, p. 54–61.

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