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The most powerful and precise AI in structural heart

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7 years of research in AI and computer vision tailored to cardiac interventions

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Several Patented Deep Learning Technologies

Granted Patents:

EP362987B1 | European Patent
EP362987C0 | European Patent
US11836924B2 | US Patent
US12136220B2 | US Patent

 

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Mitral and Tricuspid Regurgitation

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Aortic Stenosis

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Bicuspid Valve

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MAC

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Pacemaker Leads

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And other pathologies

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Trained on many different pathologies

and various scanner and image qualities

Powered by the largest set of expert annotations

Built up and fine-tuned at LARALAB since 2017

1,403,651

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LA.png
LV.png
LVM.png
RV.png
RA.png
PV.png
PA.png
Aasc.png
AorticRoot.png
BCA.png
LCCA.png
LCA.png
LAA.png
CS.png
SVC.png
IVC.png
RCA.png
LCA.png
RVPapMuscles.png
LVPapAL.png
LVPapPM.png
MitralAnterior.png
MitralPosterior.png
IVF.png
AorticNCC.png
AorticRCC.png
AorticLCC.png
TricuspidLeaflets.png
Pacemaker.png
Clavicles.png
AorticImplant.png
MitralImplant.png
TricImplant.png

Over 40 cardiac structures. The largest set in the field

Segmented by various specialized Deep Learning models

Viewing imaging data in 3D beyond the human eye

Enabled by the immense GPU power in LARALAB's scaleable cloud infrastructure

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Reaching highest precision

Proven by extensive performance testing against renowned clinical experts¹

Category

Benchmark: 0.89*

0.96

Dice Score:

Left Atrium

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Benchmark: 0.89*

0.96

Dice Score:

Left Atrium

CE_edited.png

Benchmark: 0.89*

0.96

Dice Score:

Left Atrium

CE_edited.png

Benchmark: 0.89*

0.96

Dice Score:

Left Atrium

CE_edited.png

Benchmark: 0.89*

0.96

Dice Score:

Left Atrium

CE_edited.png

References

[1]  LARALAB FDA Performance Study 2024 (pending submission)

[2] Habijan, M., H. Leventić, G. Irena and B. Danilo (2020). "Neural Network based Whole Heart Segmentation from 3D CT
images." International journal of electrical and computer engineering systems 11 (1): 25-31.

[3] Park, S., & Chung, M. (2021). Cardiac Segmentation on CT Images through Shape-Aware Contour Attentions

[4] Sundgaard J. V,. Juhl K.A., Kofoed K.F., Paulsen R.R., (2020) "Multi-planar whole heart segmentation of 3D CT images
using 2D spatial propagation CNN," Proc. SPIE 11313, Medical Imaging 2020: Image Processing


[5] Habijan, M., H. Leventić, G. Irena and B. Danilo (2020). "Neural Network based Whole Heart Segmentation from 3D CT
images." International journal of electrical and computer engineering systems 11 (1): 25-31.

[6] Sundgaard J. V,. Juhl K.A., Kofoed K.F., Paulsen R.R., (2020) "Multi-planar whole heart segmentation of 3D CT images
using 2D spatial propagation CNN," Proc. SPIE 11313, Medical Imaging 2020: Image Processing

★ We are continuously evaluating our performance against the state-of-the-art.
If you find a new publication, please write to us at ai-benchmark@laralab.de

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