Abstract
Primary tumors have a high likelihood of developing metastases in the liver, and early detection of these metastases is crucial for patient outcome. We propose a method based on convolutional neural networks to detect liver metastases. First, the liver is automatically segmented using the six phases of abdominal dynamic contrast-enhanced (DCE) MR images. Next, DCE-MR and diffusion weighted MR images are used for metastases detection within the liver mask. The liver segmentations have a median Dice similarity coefficient of 0.95 compared with manual annotations. The metastases detection method has a sensitivity of 99.8% with a median of two false positives per image. The combination of the two MR sequences in a dual pathway network is proven valuable for the detection of liver metastases. In conclusion, a high quality liver segmentation can be obtained in which we can successfully detect liver metastases.
Highlights
Detection of liver metastases is crucial since it improves patient outcome.[3,4,5]
Radiologists check for tumor growth and new metastases in computed tomography (CT) or magnetic resonance (MR) images
The liver metastases detection method we propose is a twostep method: a liver segmentation step followed by a lesion detection step within the segmented liver
Summary
Primary tumors, such as neuroendocrine and colorectal tumors, have a high likelihood of developing metastases in the liver.[1,2] Early detection of (new) liver metastases is crucial since it improves patient outcome.[3,4,5] To follow disease progress, radiologists check for tumor growth and new (liver) metastases in computed tomography (CT) or magnetic resonance (MR) images. While CT has long been the modality of choice in detecting and monitoring liver tumors, MRI has gained interest due to a better lesion-to-liver contrast and because it does not use ionizing radiation.[6,7] Dynamic contrast-enhanced (DCE) MR images have a high sensitivity and specificity for visual detection of liver metastases. The combination of DCE-MR and diffusion weighted (DW) MR images turns out to be even more effective in the visual detection of liver metastases and visual censoring of mimics.[8,9,10]
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