Search Results for author:
Found 14 papers, 2 papers with code
Measuring proximity to standard planes during fetal brain ultrasound scanning
This paper introduces a novel pipeline designed to bring ultrasound (US) plane pose estimation closer to clinical use for more effective navigation to the standard planes (SPs) in the fetal brain.
Why is the winner the best?
The "typical" lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning.
Understanding metric-related pitfalls in image analysis validation
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice.
Metrics reloaded: Recommendations for image analysis validation
The framework was developed in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint - a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output.
PEg TRAnsfer Workflow recognition challenge report: Does multi-modal data improve recognition?
The improvement between video/kinematic-based methods and the uni-modality ones was significant for all of the teams.
Ranked #1 on
Semantic Segmentation
on PETRAW
Kinematic Based Workflow Recognition
Segmentation Based Workflow Recognition
+4
Common Limitations of Image Processing Metrics: A Picture Story
While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation.
MIcro-Surgical Anastomose Workflow recognition challenge report
The best models achieved more than 95% AD-Accuracy for phase recognition, 80% for step recognition, 60% for activity recognition, and 75% for all granularity levels.
Surgical Data Science -- from Concepts toward Clinical Translation
We further complement this technical perspective with (4) a review of currently available SDS products and the translational progress from academia and (5) a roadmap for faster clinical translation and exploitation of the full potential of SDS, based on an international multi-round Delphi process.
Towards Generalizable Surgical Activity Recognition Using Spatial Temporal Graph Convolutional Networks
The proposed modality is based on spatial temporal graph representations of surgical tools in videos, for surgical activity recognition.
BIAS: Transparent reporting of biomedical image analysis challenges
The number of biomedical image analysis challenges organized per year is steadily increasing.
Offline identification of surgical deviations in laparoscopic rectopexy
Methods: We have introduced a new approach designed to automatically detect and distinguish surgical process deviations based on multi-dimensional non-linear temporal scaling with a hidden semi-Markov model using manual annotation of surgical processes.
Surgical Gesture Recognition with Optical Flow only
While Simonyan uses both RGB frames and dense optical flow, we use only dense optical flow representations as input to emphasize the role of motion in surgical gesture recognition, and present it as a robust alternative to kinematic data.
Why rankings of biomedical image analysis competitions should be interpreted with care
International challenges have become the standard for validation of biomedical image analysis methods.
Knowledge transfer for surgical activity prediction
We propose using knowledge transfer to compensate for data deficit and improve prediction.
