7 citations · 11 across the 2 of their papers we have counts for
4 papers
Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models
Pengbo Liu, Hu Han, Yuanqi Du +9
Purpose: Pelvic bone segmentation in CT has always been an essential step in clinical diagnosis and surgery planning of pelvic bone diseases. Existing methods for pelvic bone segme…
Segmenting Potentially Cancerous Areas in Prostate Biopsies using Semi-Automatically Annotated Data
Nikolay Burlutskiy, Nicolas Pinchaud, Feng Gu +7
Gleason grading specified in ISUP 2014 is the clinical standard in staging prostate cancer and the most important part of the treatment decision. However, the grading is subjective…
A Deep Learning Framework for Automatic Diagnosis in Lung Cancer
Nikolay Burlutskiy, Feng Gu, Lena Kajland Wilen +2
We developed a deep learning framework that helps to automatically identify and segment lung cancer areas in patients' tissue specimens. The study was based on a cohort of lung can…
Multi-Resolution Networks for Semantic Segmentation in Whole Slide Images
Feng Gu, Nikolay Burlutskiy, Mats Andersson +1
Digital pathology provides an excellent opportunity for applying fully convolutional networks (FCNs) to tasks, such as semantic segmentation of whole slide images (WSIs). However,…