Ultragreen.ai

Ultragreen.ai's Sajwan aims to light up the healthcare market with 'matcha powder' Ultragreen.ai' technology combines Verdye (Indocyanine Green, ICG) with AI-driven imaging tools, helping surgeons visualise and navigate with pinpoint accuracy, reducing risks and improving outcomes. As Sajwan expands globally from Singapore, his focus on partnerships and groundbreaking technology is driving growth, promising a brighter future in surgical precision. https://lnkd.in/eYnBsKj9 #ultragreen #ai #verdye #indocyaninegreen #icg #fluorescenceimaging #futureofhealthcare #ultragreenai

?? We are Hiring! Ultragreen.ai is hiring a Digital Engagement Specialist Location: Singapore Experience Level: 3-5 years of experience ? About UltraGreen.ai UltraGreen.ai is a pioneering company specialising in next-generation imaging solutions powered by advanced quantitative software and AI platforms. Based in Singapore, we are dedicated to transforming surgery by driving innovation and adoption through advanced technology solutions. We are offering a unique opportunity to join our growing team and play a key role in promoting and educating the market about our dynamic company across Singapore, Southeast Asia, and beyond. #ugcareers #ultragreencareers #digitalengagementspecialist #careers #ultragreenai See full job listing below on our careers page; https://lnkd.in/ezi_c7ZS

?? We are Hiring! Ultragreen.ai is hiring a Clinical Specialist – Fluorescence-Guided Surgery Location: Singapore (with extensive travel across Southeast Asia) Experience Level: Clinical expertise required About UltraGreen.ai UltraGreen.ai is at the forefront of next-generation imaging solutions, leveraging advanced quantitative software and AI platforms to revolutionise surgical and medical practices. We are dedicated to improving patient outcomes and advancing surgical techniques through innovation and collaboration with clinical experts. This is an exciting opportunity to join a growing team and play a pivotal role in introducing UltraGreen.ai’s pioneering quantification technology into surgical practice across Singapore, Southeast Asia, and beyond. #ultragreenai #ultragreencareers #clinicalspecialist #fluorescenceguidedsurgery #careeropportunity See full job listing below on our careers page; https://lnkd.in/ed9c-UM2

Parathyroid gland identification and angiography classification using simple machine learning methods Background: Near-infrared indocyanine green angiography allows experienced surgeons to reliably evaluate parathyroid gland vitality during thyroid and parathyroid operations in order to predict postoperative function. To facilitate equal performance between surgeons, we developed an automatic computational quantification method using computer vision that portrays expert interpretation of visualized parathyroid gland near-infrared indocyanine green angiographic fluorescence signals. Methods: Near-infrared indocyanine green-parathyroid gland angiography video recordings (Fluobeam? LX, Fluoptics, Grenoble-part of Getinge-G?teborg) from patients undergoing endocrine cervical surgery in a high-volume unit were used for model development. Results: The model was trained on 37 patient videos (45 glands, 29 judged well perfused by parathyroid gland angiography experts), achieving feature data separation with 100% accuracy, and tested on 22 unseen videos (27 glands, 15 judged well perfused), including four in real time. Segmentation-guided parathyroid gland detection correctly identified all parathyroid glands during unseen testing along with three additional non-parathyroid gland regions (90% positive predictive value). Subsequent time-fluorescence intensity profile extraction with vitality prediction was shown feasible in all cases within 5 min, with a 96.3% model accuracy (sensitivity and specificity were 93.3 and 100% respectively) when compared with expert judgement. Conclusion: Automatic parathyroid gland perfusion quantification using simple machine learning computational methods discriminates parathyroid gland perfusion in concordance with expert surgeon interpretation, providing a means for near-infrared indocyanine green-parathyroid gland signal evaluation. https://lnkd.in/ejwwGb7W #parathyroidglandidentification #angiography #machinelearning #nir #icga #healthtech #ultragreen

A feasibility study assessing quantitative indocyanine green angiographic predictors of reconstructive complications following nipple-sparing mastectomy Immediate post-mastectomy breast reconstruction offers benefits; however, complications can compromise outcomes. Intraoperative indocyanine green fluorescence angiography (ICGFA) may mitigate perfusion-related complications (PRC); however, its interpretation remains subjective. Here, we examine and develop methods for ICGFA quantification, including machine learning (ML) algorithms for predicting complications. doi: 10.1016/j.jpra.2024.01.012 #icgfa #prc #quantitativeicga #nipplesparingmastectomy #indocyaninegreen #quantification #betterpatientoutcomes #verdye #ultragreen

Intraoperative near infrared functional imaging of rectal cancer using artificial intelligence methods - now and near future state of the art Colorectal cancer remains a major cause of cancer death and morbidity worldwide. Surgery is a major treatment modality for primary and, increasingly, secondary curative therapy. However, with more patients being diagnosed with early stage and premalignant disease manifesting as large polyps, greater accuracy in diagnostic and therapeutic precision is needed right from the time of first endoscopic encounter. Rapid advancements in the field of artificial intelligence (AI), coupled with widespread availability of near infrared imaging (currently based around indocyanine green (ICG)) can enable colonoscopic tissue classification and prognostic stratification for significant polyps, in a similar manner to contemporary dynamic radiological perfusion imaging but with the advantage of being able to do so directly within interventional procedural time frames. #rectalcancer #nirf #nearinfraredimaging #ai #artificialintelligence #icg #indocyaninegreen #perfusionassessment #ultragreen doi: 10.1007/s00259-024-06731-9

ICG & Quantification - Advancing indocyanine green fluorescence flap perfusion assessment via near infrared signal quantification Intraoperative indocyanine green fluorescence angiography (ICGFA) perfusion assessment has been demonstrated to reduce complications in reconstructive surgery. This study sought to advance ICGFA flap perfusion assessment via quantification methodologies. Fifteen patients underwent ICGFA assessment at reconstruction (8 head and neck, 6 breast and 1 perineum) including 10 free and 5 pedicled flaps. Visual ICGFA interpretation altered on-table management in 33.3% of cases, with flap edges trimmed in 4 and a re-anastomosis in 1 patient. One patient suffered post-operative flap dehiscence. Laparoscopic camera use proved feasible but recorded a lower quality signal than the open system. Using established and novel metrics, objective ICGFA signal ROI quantification permitted perfusion comparisons between the flap and surrounding tissue. This trial demonstrated the feasibility and potential for ICGFA with operator based and quantitative flap perfusion assessment across several reconstructive applications. doi: 10.1016/j.jpra.2024.05.005 #flapperfusion #perfusionassessment #reconstructivesurgery #icg #quantification #icgfa #indocyaninegreen #verdye #diagnosticgreen

Our Vision Ultragreen.ai was established to provide the next generation of high-quality imaging solutions. Explore our website to learn how we’re shaping the next generation of imaging solutions and join us on this exciting journey. https://ultragreen.ai/ #visionfortomorrow #betterpatientoutcomes #shapingourhealthcarefuture #imagingsolutions #fluorescence #fluorescenceimaging #ultragreen