Automated Sperm Tracking and Immobilization With a Clinically-Compatible XYZ Stage
Bibliographic record
Abstract
Automated positioning systems play a pivotal role in micro-scale cell manipulation. In clinical intracytoplasmic sperm injection (ICSI) for infertility treatment, a motile sperm needs to be immobilized by glass micropipette tapping for subsequent surgical steps. The process requires accurate tracking of the target sperm and precise alignment between the sperm tail and the micropipette. Manual sperm immobilization suffers from inconsistent success rates, and current robotic systems developed for the task fail to comply with the standard clinical setup. Instead of using a motorized micromanipulator as in existing robotic systems, this paper presents an automated and compact three-dimensional (3-D) positioning stage for sperm immobilization that can be seamlessly integrated into standard clinical platforms. To tackle the challenge of accurately tracking the target sperm with degraded detection quality due to the complex 3-D motion of the positioning stage, a multi-stage sperm tracking scheme is designed for detection-to-tracklet association. To prevent physical contact between the sperm head and the micropipette, an adaptive tail-tapping planning strategy based on the sperm head orientation analysis is established. A visual servo controller equipped with a dynamic sperm motion observer is further employed to achieve precise positioning of the target sperm during the immobilization process. Experimental results demonstrated that the proposed system achieved a sperm tracking accuracy of 88.12%, and a sperm positioning accuracy of$2.3~\pm ~1.2~\mu $m. Further experiments revealed the system achieved a success rate of 93.5% and a time cost of 5.5 s for automated sperm immobilization. Note to Practitioners—This work presents an automated positioning system for the robotic immobilization of live human sperm in the intracytoplasmic sperm injection (ICSI) process. Conventional robotic systems developed for sperm immobilization use motorized stages which only provide two degrees of freedom (DOF) and disturb standard clinical setups with bulky sizes and additional equipment. Leveraging the advantages of piezoelectric positioners, a compact 3-D positioning system is developed to perform robotic sperm immobilization in an all-in-one manner. A sperm immobilization tracker is developed to track the target sperm during the immobilization process. The proposed multi-stage data association metric can effectively resist the noisy detection results due to occlusion and out-of-focus blur introduced by the 3-D movement of the positioning stage. Based on the analysis of the sperm head orientation, an adaptive tail-tapping planning strategy is established to avoid the risk of contacting the sperm head where DNA is contained. The developed positioning system can be easily integrated into a standard microscopy operation platform for biological cell manipulation. The proposed tracking scheme is applicable in various microscopy cell analysis scenarios where the detection results are inevitably affected by the degraded image quality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".