1 code implementation • 12 Feb 2018 • Nathan Lay, Adam P. Harrison, Sharon Schreiber, Gitesh Dawer, Adrian Barbu
We propose random hinge forests, a simple, efficient, and novel variant of decision forests.
no code implementations • 31 Jan 2017 • Holger R. Roth, Le Lu, Nathan Lay, Adam P. Harrison, Amal Farag, Andrew Sohn, Ronald M. Summers
Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging problem for medical image analysis.
Ranked #1 on 3D Medical Imaging Segmentation on TCIA Pancreas-CT
no code implementations • 14 Apr 2014 • Adrian Barbu, Nathan Lay, Gary Gramajo
This paper presents a part-based face detection approach where the spatial relationship between the face parts is represented by a hidden 3D model with six parameters.
no code implementations • 6 Jan 2023 • Pouria Yazdian Anari, Nathan Lay, Aditi Chaurasia, Nikhil Gopal, Safa Samimi, Stephanie Harmon, Rabindra Gautam, Kevin Ma, Fatemeh Dehghani Firouzabadi, Evrim Turkbey, Maria Merino, Elizabeth C. Jones, Mark W. Ball, W. Marston Linehan, Baris Turkbey, Ashkan A. Malayeri
Our 2D U-Net achieved an average ccRCC lesion detection Area under the curve (AUC) of 0. 88 and DSC scores of 0. 78, 0. 40, and 0. 46 for segmentation of the kidney, cysts, and tumors, respectively.
no code implementations • 8 Feb 2024 • Pouria Yazdian Anari, Fiona Obiezu, Nathan Lay, Fatemeh Dehghani Firouzabadi, Aditi Chaurasia, Mahshid Golagha, Shiva Singh, Fatemeh Homayounieh, Aryan Zahergivar, Stephanie Harmon, Evrim Turkbey, Rabindra Gautam, Kevin Ma, Maria Merino, Elizabeth C. Jones, Mark W. Ball, W. Marston Linehan, Baris Turkbey, Ashkan A. Malayeri
The best primary model was then used to identify tumors in the remaining 861 patients and bounding box coordinates were generated on their scans using the model.