Daniel Haehn PRO
Hi, I am a biomedical imaging and visualization researcher who investigates how computational methods can accelerate biological and medical research.
The Oregon-Massachusetts Mammography Database
Bits to Bytes
Daniel Haehn
Nurit Haspel
Alexey Tonyushkin
Marc Pomplun
Dan Simovici
Bill Lotter
Greg Sorensen
5/5/2020
Haehn et al.: The Oregon-Massachusetts Mammography Database (OMAMA-DB)
World's Largest Publicly-Available Annotated Mammography Dataset
70,000 imaging studies with ground truth labels
acquired data over 9 years
GE (63%), Hologic (37%)
50,000 mammograms
20,000 tomosynthesis
no tomosynthesis
> 95% Hologic
proprietary
Haehn et al.: The Oregon-Massachusetts Mammography Database (OMAMA-DB)
manual annotation of 70,000 studies is not feasible
Intelligent Annotation Framework
Two Artificial Neural Networks..
..work together for Quality control
Discriminator finds error pattern of Classifier
Haehn et al.: The Oregon-Massachusetts Mammography Database (OMAMA-DB)
Intelligent Annotation Framework
can tune classifiers beyond breast cancer
open source from the start
algorithmic contribution
Breast Cancer Database
will spur automatic detection advances
challenge datasets
raw data available right now
70,000 annotations in the first 2 years
Newest GPUs in UMass Boston's GPU Cluster are 6 years old
Excellent training opportunities for the most diverse student population in New England
Haehn et al.: The Oregon-Massachusetts Mammography Database (OMAMA-DB)
3 PhD Students
1 Data Scientist
Undergraduate Students
DeepHealth successfully works with a team of 4 students
Haehn et al.: The Oregon-Massachusetts Mammography Database (OMAMA-DB)
Dr. Marco Nolden
Dr. Ron Kikinis
Dr. Regina Barzilay
Dr. Jill Macoska
Dr. Gordon Harris
Dr. Mansi Saksena
Genomics Data
Breast MRI Data
Lymphoma Data
Knowledge Transfer (Year 3)
Haehn et al.: The Oregon-Massachusetts Mammography Database (OMAMA-DB)
Algorithmic Research at UMass Boston
AI Implementation at UMass Memorial
More Data
Intelligent Annotations
Questions?
Haehn et al.: The Oregon-Massachusetts Mammography Database (OMAMA-DB)
More Annotations...
Dr. Steve Pieper
paired with expert validations
Haehn et al., CVPR 2018
post-training optimization of GP acc.
from 0.5982 to 0.9087
Preliminary Results
Haehn et al.: The Oregon-Massachusetts Mammography Database (OMAMA-DB)
Not-for-profit sharing after project completion!
| NVidia DGX-2 AI Supercomputer | $303,851.00 |
| 5x Annotation Workstations | $32,527.95 |
| 5x Wacom Tablets | $2,049.80 |
| 18 Terabyte Dedicated Storage | $28,244.74 |
| DeepSight Software | $374,000.00 |
| Total Requested | $740,673.00 |
Haehn et al.: The Oregon-Massachusetts Mammography Database (OMAMA-DB)
B2B
By Daniel Haehn
B2B
The Oregon-Massachusetts Mammography Database
