Interactive Outlining of Pancreatic Cancer Liver Metastases in Ultrasound Images
원문 초록
Ultrasound (US) is the most commonly used liver imaging modality worldwide. Due to its low cost, it is increasingly used in the follow-up of cancer patients with metastases localized in the liver. In this contribution, we present the results of an interactive segmentation approach for liver metastases in US acquisitions. A (semi-) automatic segmentation is still very challenging because of the low image quality and the low contrast between the metastasis and the surrounding liver tissue. Thus, the state of the art in clinical practice is still manual measurement and outlining of the metastases in the US images. We tackle the problem by providing an interactive segmentation approach providing real-time feedback of the segmentation results. The approach has been evaluated with typical US acquisitions from the clinical routine, and the datasets consisted of pancreatic cancer metastases. Even for difficult cases, satisfying segmentations results could be achieved because of the interactive real-time behavior of the approach. In total, 40 clinical images have been evaluated with our method by comparing the results against manual ground truth segmentations. This evaluation yielded to an average Dice Score of 85% and an average Hausdorff Distance of 13 pixels.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Seg-Wild: Interactive Segmentation based on 3D Gaussian Splatting for Unconstrained Image Collections
DC-TTA: Divide-and-Conquer Framework for Test-Time Adaptation of Interactive Segmentation
TSDASeg: A Two-Stage Model with Direct Alignment for Interactive Point Cloud Segmentation
SafeClick: Error-Tolerant Interactive Segmentation of Any Medical Volumes via Hierarchical Expert Consensus
Zero-Shot Gaze-based Volumetric Medical Image Segmentation
TAGS: 3D Tumor-Adaptive Guidance for SAM
토론
이 논문과 연결된 포럼 글이 아직 없습니다.