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Cataract Surgery and Complications
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Cataract Surgery and Complications

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Ophthalmology".

Deadline for manuscript submissions: closed (25 September 2020) | Viewed by 2539

Special Issue Editor

Dr. Hitoshi Tabuchi

E-Mail Website
Guest Editor
1. Department of Ophthalmology, Tsukazaki Hospital, 68-1 Waku, Aboshi-ku, Himeji 671-1227, Japan
2. Department of Technology and Design Thinking for Medicine, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551, Japan
Interests: cataract surgery; ICT; ophthalmology; clinical surgery; refractive Surgery; ocular circulation; strabismus; amblyopia; neuro-ophthalmology; pediatric ophthalmology; ophthalmic surgery; glaucoma; retina
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Advances in cataract surgery are directly linked to advances in ophthalmic medicine as a whole. The shortening of the learning curve in cataract surgery education has been an eternal theme, and one recent emerging problem is the increase in the number of cases of intraocular lens fall due to ruptured chin zonules. Moreover, patient dissatisfaction with premium intraocular lens is an additional new complication. In this Special Issue, we would like to explore ambitious approaches applied toward cataract surgery and complications. As clinical research methods enter a new era, we would anticipate submissions involving research that uses artificial intelligence technology as an objective measurement method.

Dr. Hitoshi Tabuchi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • surgical outcomes
  • cataract surgical education
  • learning curve
  • multifocal intraocular lenses
  • toric intraocular lenses
  • patient satisfaction
  • IOL power calculation
  • intrascleral fixation
  • dislocation of intraocular lens
  • artificial intelligence
  • deep learning

Published Papers (1 paper)

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Research

17 pages, 4424 KiB  
Article
Real-Time Surgical Problem Detection and Instrument Tracking in Cataract Surgery
by Shoji Morita, Hitoshi Tabuchi, Hiroki Masumoto, Hirotaka Tanabe and Naotake Kamiura
J. Clin. Med. 2020, 9(12), 3896; https://doi.org/10.3390/jcm9123896 - 30 Nov 2020
Cited by 9 | Viewed by 2091
Abstract
Surgical skill levels of young ophthalmologists tend to be instinctively judged by ophthalmologists in practice, and hence a stable evaluation is not always made for a single ophthalmologist. Although it has been said that standardizing skill levels presents difficulty as surgical methods vary [...] Read more.
Surgical skill levels of young ophthalmologists tend to be instinctively judged by ophthalmologists in practice, and hence a stable evaluation is not always made for a single ophthalmologist. Although it has been said that standardizing skill levels presents difficulty as surgical methods vary greatly, approaches based on machine learning seem to be promising for this objective. In this study, we propose a method for displaying the information necessary to quantify the surgical techniques of cataract surgery in real-time. The proposed method consists of two steps. First, we use InceptionV3, an image classification network, to extract important surgical phases and to detect surgical problems. Next, one of the segmentation networks, scSE-FC-DenseNet, is used to detect the cornea and the tip of the surgical instrument and the incisional site in the continuous curvilinear capsulorrhexis, a particularly important phase in cataract surgery. The first and second steps are evaluated in terms of the area under curve (i.e., AUC) of the figure of the true positive rate versus (1—false positive rate) and the intersection over union (i.e., IoU) obtained by the ground truth and prediction associated with the region of interest. As a result, in the first step, the network was able to detect surgical problems with an AUC of 0.97. In the second step, the detection rate of the cornea was 99.7% when the IoU was 0.8 or more, and the detection rates of the tips of the forceps and the incisional site were 86.9% and 94.9% when the IoU was 0.1 or more, respectively. It was thus expected that the proposed method is one of the basic techniques to achieve the standardization of surgical skill levels. Full article
(This article belongs to the Special Issue Cataract Surgery and Complications)
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