activity
20232026
most citedDetection-Guided Deep Learning-Based Model with Spatial Regularization for Lung Nodule Segmentation

10 citations · 15 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Multitask Conditional Generative Adversarial Network Enables Automatic Whole Knee Cartilage and Menisci Segmentation and Reliable and Quantification Without High-Resolution Morphological Images

Ahmed Tahseen Minhaz, Richard Lartey, Zhiyuan Zhang +8

Early osteoarthritis detection through quantitative MRI (qMRI) requires accurate cartilage and meniscus segmentation, traditionally necessitating time-consuming, costly 3D high-res…

q-bio.QM2025★ 4 cited

Towards Quantum Tensor Decomposition in Biomedical Applications

Myson Burch, Jiasen Zhang, Gideon Idumah +12

Tensor decomposition has emerged as a powerful framework for feature extraction in multi-modal biomedical data. In this review, we present a comprehensive analysis of tensor decomp…

cs.CV2024★ 10 cited

Detection-Guided Deep Learning-Based Model with Spatial Regularization for Lung Nodule Segmentation

Jiasen Zhang, Mingrui Yang, Weihong Guo +3

Lung cancer ranks as one of the leading causes of cancer diagnosis and is the foremost cause of cancer-related mortality worldwide. The early detection of lung nodules plays a pivo…

cs.CV2023

A Geometric Flow Approach for Segmentation of Images with Inhomongeneous Intensity and Missing Boundaries

Paramjyoti Mohapatra, Richard Lartey, Weihong Guo +2

Image segmentation is a complex mathematical problem, especially for images that contain intensity inhomogeneity and tightly packed objects with missing boundaries in between. For…

eess.IV2023★ 1 cited

Interpretable Small Training Set Image Segmentation Network Originated from Multi-Grid Variational Model

Junying Meng, Weihong Guo, Jun Liu +1

The main objective of image segmentation is to divide an image into homogeneous regions for further analysis. This is a significant and crucial task in many applications such as me…