Congrats to Jeremy and Colin for their ISBI 2018 paper on Connectome Priors in Deep Neural Networks to Predict Autism
Congrats to Saeed, Zahra and Jeremy for their ISBI 2018 paper on Generative Adversarial Networks to Segment Skin Lesions.
Congrats to Zahra, Saeed and Jeremy for their ISBI 2018 paper on Deep Auto-context Fully Convolutional Neural Network for Skin Lesion Segmentation.
Congrats to Saeid and Noirin for their CMIG paper on Segmentation-Free Direct Tumor Volume and Metabolic Activity Estimation from PET Scans.
Ismail’s work on network modelling and machine learning for analyzing single molecule localization microscopy of prostate cancer super-resolution data: https://www.cs.sfu.ca/~hamarneh/bib/author/KHATER-IM.html
Congrats to Aïcha for her new IEEE TMI paper on Adversarial Stain Transfer for Histopathology Image Analysis
Our work IEEE JBHI work (DOI) is featured on the Medical Physics Web: "From photo, to 3D model, through to wound healing"
Congrats Mian for winning the best spotlight presentation award at MICCAI LABELS workshop
Title: SwifTree: Interactive Extraction of 3D Trees Supporting Gaming and Crowdsourcing
Congrats Saeed for Winning 2nd place in the Gastrointestinal Image ANAlysis (GIANA) sub-challenge for the polyp segmentation task, as a part of EndoVis challenge, MICCAI 2017. See press release.
Title: Adversarial Networks for Gastrointestinal Polyp Segmentation in Endoscopic Images
Winners of Polyp Segmentation awards. From left to right, Bogdan J. Matuszewski (CVML. 1st prize), Aïcha Bentaieb accepting the award on behalf of Saeed Izadi (SFU, 2nd prize), Vladimir Iglovikov (TA-MIT, 3rd prize) and Danail Stoyanov (UCL, 3rd prize).
New paper published:
Segmentation and Measurement of Chronic Wounds for Bioprinting, IEEE Journal of Biomedical and Health Informatics (IEEE JBHI)
Prof. Hamarneh awarded 4-year funding from BCCA and BrainCare for working on Medical Image Analysis and Machine Learning for Management of Malignant Brain Tumours.
Congrats to students Zahra, Mengliu, Kathleen, Jeremy, Aïcha, Mian, Colin and Arafat, for their papers accepted for presentation at MICCAI 2017 and its workshops:
MICCAI - Globally-Optimal Anatomical Tree Extraction from 3D Medical Images using Pictorial Structures and Minimal Paths.
MICCAI - Prediction of Brain Network Age and Factors of Delayed Maturation in Very Preterm Infants.
MICCAI LABELS - Uncertainty Driven Multi-Loss Fully Convolutional Networks for Gland Analysis.
MICCAI LABELS - SwifTree: Interactive Extraction of 3D Trees Supporting Gaming and Crowdsourcing.
MICCAI GRAIL - Graph Geodesics to Find Progressively Similar Skin Lesion Images.
MICCAI MLMI - Collage CNN for Renal Cell Carcinoma Detection from CT
Prediction of Brain Network Age and Factors of Delayed Maturation in Very Preterm Infants
at the UBC MRI Research Groups 11th Annual Retreat
Congratulations to Jeremy for being awarded "Graduate Prize in Computing Science" (top CS graduate student).
Congratulations to Colin and Roja for their Brachytherapy journal paper on
Association of Bladder Dose with Late Urinary Side Effects in Cervical Cancer HDR brachytherapy Brachytherapy
Our contribution on Multi‐site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data was selected as one of the highlights appearing under the Editors' Choice column for the Medical Physics Scitation and medphys.org websites
Our lab participated in the 2nd Annual Health Technology Symposium in Vancouver
Topology Aware Fully Convolutional Networks for Histology Gland Segmentation
Tumor Lesion Segmentation from 3D PET using a Machine Learning driven Active Surface
BrainNetCNN: Artificial Convolutional Neural Networks for Connectomes
Filtering, Segmenting, and Quantifying Caveolin-1 Protein Clusters in 3D SuperResolution Microscopy via Machine-Learning and Network Analysis
Globally-Optimal Anatomical Tree Extraction from 3D Medical Images using Pictorial Structures and Minimal Paths
Tree Structure Analysis in 3D Medical Images
Saeid’s work presented at the Quantitative Imaging Network (QIN) Annual Meeting, 2017: Lesion volume Estimation from PET without Requiring Segmentation
Mengliu's work awarded an Honourable Mention for Best Computer Vision Paper at the 2017 Conference on Computer and Robot Vision (CRV) for her work on Leveraging Tree Statistics for Extracting Anatomical Trees from 3D Medical Images
Mengliu presented two papers at the 2017 Conference on Computer and Robot Vision (CRV)
New software released supporting the work:
A Structured Latent Model for Ovarian Carcinoma Subtyping from Histopathology Slides
The code is available at here.
Congratulations to Jeremey for achieving the score in Part 2 - clinical feature detection of the International Skin Imaging Collaboration (ISIC) skin lesion analysis challenge, in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI), and invited for an oral presentation at ISBI 2017 in Melbourne, Australia.
Congratulations to Aïcha for her new J.MedIA paper on
Contextual Representation of Histopathology Slides for Automatic Ovarian Carcinoma Diagnosis
Congratulations to Colin for judges' choice award and Payam for people's choice award in the faculty of applied science three minute thesis.