1 citations · 1 across the 4 of their papers we have counts for
4 papers
PSHop: A Lightweight Feed-Forward Method for 3D Prostate Gland Segmentation
Yijing Yang, Vasileios Magoulianitis, Jiaxin Yang +8
Automatic prostate segmentation is an important step in computer-aided diagnosis of prostate cancer and treatment planning. Existing methods of prostate segmentation are based on d…
PCa-RadHop: A Transparent and Lightweight Feed-forward Method for Clinically Significant Prostate Cancer Segmentation
Vasileios Magoulianitis, Jiaxin Yang, Yijing Yang +8
Prostate Cancer is one of the most frequently occurring cancers in men, with a low survival rate if not early diagnosed. PI-RADS reading has a high false positive rate, thus increa…
A Tiny Machine Learning Model for Point Cloud Object Classification
Min Zhang, Jintang Xue, Pranav Kadam +3
The design of a tiny machine learning model, which can be deployed in mobile and edge devices, for point cloud object classification is investigated in this work. To achieve this o…
S3I-PointHop: SO(3)-Invariant PointHop for 3D Point Cloud Classification
Pranav Kadam, Hardik Prajapati, Min Zhang +3
Many point cloud classification methods are developed under the assumption that all point clouds in the dataset are well aligned with the canonical axes so that the 3D Cartesian po…