Keyword search (4,163 papers available)

"Dataset" Keyword-tagged Publications:

Title Authors PubMed ID
1 ADPv2: A hierarchical histological tissue type-annotated dataset for potential biomarker discovery of colorectal disease Yang Z; Li K; Ramandi SG; Brassard P; Khellaf A; Trinh VQ; Zhang J; Chen L; Rowsell C; Varma S; Plataniotis K; Hosseini MS; 41658283
ENCS
2 CACTUS: An open dataset and framework for automated Cardiac Assessment and Classification of Ultrasound images using deep transfer learning Elmekki H; Alagha A; Sami H; Spilkin A; Zanuttini AM; Zakeri E; Bentahar J; Kadem L; Xie WF; Pibarot P; Mizouni R; Otrok H; Singh S; Mourad A; 40107020
ENCS
3 MuscleMap: An Open-Source, Community-Supported Consortium for Whole-Body Quantitative MRI of Muscle McKay MJ; Weber KA; Wesselink EO; Smith ZA; Abbott R; Anderson DB; Ashton-James CE; Atyeo J; Beach AJ; Burns J; Clarke S; Collins NJ; Coppieters MW; Cornwall J; Crawford RJ; De Martino E; Dunn AG; Eyles JP; Feng HJ; Fortin M; Franettovich Smith MM; Galloway G; Gandomkar Z; Glastras S; Henderson LA; Hides JA; Hiller CE; Hilmer SN; Hoggarth MA; Kim B; Lal N; LaPorta L; Magnussen JS; Maloney S; March L; Nackley AG; O' Leary SP; Peolsson A; Perraton Z; Pool-Goudzwaard AL; Schnitzler M; Seitz AL; Semciw AI; Sheard PW; Smith AC; Snodgrass SJ; Sullivan J; Tran V; Valentin S; Walton DM; Wishart LR; Elliott JM; 39590726
HKAP
4 CosSIF: Cosine similarity-based image filtering to overcome low inter-class variation in synthetic medical image datasets Islam M; Zunair H; Mohammed N; 38492455
ENCS
5 Firefly (Coleoptera, Lampyridae) species from the Atlantic Forest hotspot, Brazil Vaz S; Mendes M; Khattar G; Macedo M; Ronquillo C; Zarzo-Arias A; Hortal J; Silveira L; 38327309
CONCORDIA
6 Analysis of input set characteristics and variances on k-fold cross validation for a Recurrent Neural Network model on waste disposal rate estimation Vu HL; Ng KTW; Richter A; An C; 35287077
ENCS
7 Multimodal 3D ultrasound and CT in image-guided spinal surgery: public database and new registration algorithms Masoumi N; Belasso CJ; Ahmad MO; Benali H; Xiao Y; Rivaz H; 33683544
PERFORM
8 Augmented reality mastectomy surgical planning prototype using the HoloLens template for healthcare technology letters. Amini S, Kersten-Oertel M 32038868
PERFORM

 

Title:Augmented reality mastectomy surgical planning prototype using the HoloLens template for healthcare technology letters.
Authors:Amini SKersten-Oertel M
Link:https://www.ncbi.nlm.nih.gov/pubmed/32038868?dopt=Abstract
DOI:10.1049/htl.2019.0091
Publication:Healthcare technology letters
Keywords:HoloLens templateaugmented realityaugmented reality applicationaugmented reality mastectomy surgical planning prototypeavailable implantsbreast reconstructioneliminates sizer implantshealth carehealthcare technology lettersholographic implantsimage reconstructionmeasurement toolsmedical computingmedical image processingmultiple implantsprostheticssingle mastectomysingle patientsurgeonsurgerysystem datasettraditional waytwo-chamber implant
PMID:32038868 Category:Healthc Technol Lett Date Added:2020-02-11
Dept Affiliation: PERFORM
1 Department of Computer Science and Software Engineering, Concordia University, Montréal, QC, Canada H3G 2V8.
2 PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6.

Description:

Augmented reality mastectomy surgical planning prototype using the HoloLens template for healthcare technology letters.

Healthc Technol Lett. 2019 Dec;6(6):261-265

Authors: Amini S, Kersten-Oertel M

Abstract

In breast reconstruction following a single mastectomy, the surgeon needs to choose between tens of available implants to find the one that can reproduce the symmetry of the patient's breasts. However, due to the lack of measurement tools this decision is made purely visually, which means the surgeon has to order multiple implants to confirm the size for every single patient. In this Letter, the authors present an augmented reality application, which enables surgeons to see the shape of the implants, as 3D holograms on the patient's body. They custom developed a two-chamber implant that can gain different shapes and be used to test the system. Furthermore, the system was tested in a user study with 13 subjects. The study showed that subjects were able to do a comparison between real and holographic implants and come to a decision about which should be used. This method can be quicker than the traditional way and eliminates sizer implants from the process. Further advantages of the method include the use of a more accurate, user-friendly device, which is easily extendable as new implants that are on the market can be easily added to the system dataset.

PMID: 32038868 [PubMed]





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