27 research outputs found

    Can surgical simulation be used to train detection and classification of neural networks?

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    Computer-assisted interventions (CAI) aim to increase the effectiveness, precision and repeatability of procedures to improve surgical outcomes. The presence and motion of surgical tools is a key information input for CAI surgical phase recognition algorithms. Vision-based tool detection and recognition approaches are an attractive solution and can be designed to take advantage of the powerful deep learning paradigm that is rapidly advancing image recognition and classification. The challenge for such algorithms is the availability and quality of labelled data used for training. In this Letter, surgical simulation is used to train tool detection and segmentation based on deep convolutional neural networks and generative adversarial networks. The authors experiment with two network architectures for image segmentation in tool classes commonly encountered during cataract surgery. A commercially-available simulator is used to create a simulated cataract dataset for training models prior to performing transfer learning on real surgical data. To the best of authors' knowledge, this is the first attempt to train deep learning models for surgical instrument detection on simulated data while demonstrating promising results to generalise on real data. Results indicate that simulated data does have some potential for training advanced classification methods for CAI systems

    Rapid resolution of severe sustained low blood pressure in haemodialysis patients after successful renal transplantation

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    Background Low blood pressure occurring in the absence of volume depletion, anti-hypertensive medication, heart failure or cortisol deficiency occurs in ∼5–10% of haemodialysis patients, and can result in serious complications. The pathophysiology of this syndrome is poorly understood. Methods We describe eight cases with dialysis-associated hypotension who underwent renal transplantation. Four patients were severely hypotensive with a systolic blood pressure (SBP) 100 mmHg between sessions. All had donor-specific human leukocyte antigen antibodies. Six patients underwent pre-transplant plasmapheresis, which was curtailed in two because of further falls in blood pressure. Two patients experienced clotting of their arteriovenous fistula. In one patient cryofiltration was used, which was tolerated without severe falls in the BP. The remaining patient, who had hypotension-associated retinal vein thrombosis before transplant, was supported with an epinephrine infusion and did not receive plasmapheresis. Results Post-transplant, the first patient did not receive pressor therapy and died from bowel ischaemia. The other seven patients were supported with inotropes on critical care. The administration of steroids did not reverse hypotension. The mean pre-treatment SBP was 96 mmHg (range 71–110, SEM 5.0). After inotropes were withdrawn and graft function was established, the mean SBP was 127 mmHg (range 113–149, SEM 4.9) (P < 0.01). Conclusions Renal transplantation was performed successfully and safely in patients when pressor therapy was used to treat severe dialysis-associated hypotension and, moreover, the blood pressure normalized rapidly after graft function was established
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