Lotta M. Ellingsen - Publications

Automated neural network femur segmentation performance in computed tomography images of older adults with obesity.

Journal: JBMR plus

Published: September 10, 2025

Region-based U-nets for fast, accurate, and scalable deep brain segmentation: Application to Parkinson Plus Syndromes.

Journal: NeuroImage. Clinical

Published: March 04, 2025

Comparison of the time-dependent discriminatory accuracy of femoral strength and bone mineral density for predicting future hip and major osteoporotic fractures: a 16-year follow-up of the AGES-Reykjavik cohort.

Journal: Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA

Published: November 12, 2024

Segmentation methods for quantifying X-ray Computed Tomography based biomarkers to assess hip fracture risk: a systematic literature review.

Journal: Frontiers in bioengineering and biotechnology

Published: June 10, 2024

Automated fingerprint analysis as a diagnostic tool for the genetic disorder Kabuki syndrome.

Journal: Genetics in medicine open

Published: February 09, 2024

A joint ventricle and WMH segmentation from MRI for evaluation of healthy and pathological changes in the aging brain.

Journal: PloS one

Published: February 01, 2022

Introducing a gatekeeping system for amyloid status assessment in mild cognitive impairment.

Journal: European journal of nuclear medicine and molecular imaging

Published: January 12, 2022

SegAE: Unsupervised white matter lesion segmentation from brain MRIs using a CNN autoencoder.

Journal: NeuroImage. Clinical

Published: July 05, 2019

Brain age prediction using deep learning uncovers associated sequence variants.

Journal: Nature communications

Published: April 02, 2019

Applications of a deep learning method for anti-aliasing and super-resolution in MRI.

Journal: Magnetic resonance imaging

Published: December 29, 2018

Brain ventricle parcellation using a deep neural network: Application to patients with ventriculomegaly.

Journal: NeuroImage. Clinical

Published: December 05, 2018

Shortcomings of Ventricle Segmentation Using Deep Convolutional Networks.

Journal: Understanding and interpreting machine learning in medical image computing applications : first international workshops, MLCN 2018, DLF 2018, and iMIMIC 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 16-20, 2018 :...

Published: September 01, 2018