Manual Small-Incision Cataract Surgery ({SICS}) is a prevalent technique in low- and middle-income countries ({LMICs}) but understudied with respect to computer assisted surgery. This prospective cross-sectional study introduces the first {SICS} video dataset, evaluates effectiveness of phase recognition through deep learning ({DL}) using the {MS}-{TCN} + + architecture, and compares its results with the well-studied phacoemulsification procedure using the Cataract-101 public dataset. Our novel {SICS}-105 dataset involved 105 patients recruited at Sankara Eye Hospital in India. Performance is evaluated with frame-wise accuracy, edit distance, F1-score, Precision-Recall {AUC}, sensitivity, and specificity. The {MS}-{TCN} + + architecture performs better on the Cataract-101 dataset, with an accuracy of 89.97\\% [{CI} 86.69\u201393.46\\%] compared to 85.56\\% [80.63\u201392.09\\%] on the {SICS}-105 dataset ({ROC} {AUC} 99.10\\% [98.34\u201399.51\\%] vs. 98.22\\% [97.16\u201399.26\\%]). The accuracy distribution and confidence-intervals overlap and the {ROC} {AUC} values range 46.20 to 94.18\\%. Even though {DL} is found to be effective for phase recognition in {SICS}, the larger number of phases and longer duration makes it more challenging compared to phacoemulsification. To support further developments, we make our dataset open access. This research marks a crucial step towards improving postoperative analysis and training for {SICS}.<\/p>\n","protected":false},"excerpt":{"rendered":"
Manual Small-Incision Cataract Surgery ({SICS}) is a prevalent technique in low- and middle-income countries ({LMICs}) but understudied with respect to computer assisted surgery. This prospective cross-sectional study introduces the first {SICS} video dataset, evaluates effectiveness of phase recognition through deep learning ({DL}) using the {MS}-{TCN} + + architecture, and compares its results with the well-studied phacoemulsification procedure using the Cataract-101 public dataset. Our novel {SICS}-105 dataset involved 105 patients recruited […]<\/p>\n","protected":false},"author":12,"featured_media":0,"template":"","meta":{"_acf_changed":false,"footnotes":""},"publication-type":[30],"class_list":["post-32279","publication","type-publication","status-publish","hentry","publication-type-article"],"acf":[],"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication\/32279","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication"}],"about":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/types\/publication"}],"author":[{"embeddable":true,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/users\/12"}],"version-history":[{"count":0,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication\/32279\/revisions"}],"wp:attachment":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/media?parent=32279"}],"wp:term":[{"taxonomy":"publication-type","embeddable":true,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication-type?post=32279"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}