434 citations
- Chinese Academy of SciencesCN16 papers
- Shanghai Astronomical ObservatoryCN12 papers
- Sun Yat-sen UniversityCN11 papers
- École de Technologie SupérieureCA10 papers
- Guangxi Key Laboratory of Optoelectronic Information ProcessingCN10 papers
- Guilin University of TechnologyCN8 papers
- Taibah UniversitySA6 papers
- Tsinghua UniversityCN6 papers
- Centre National de la Recherche ScientifiqueFR5 papers
- Dongguan University of TechnologyCN5 papers
- Harbin Institute of TechnologyCN5 papers
- Peng Cheng LaboratoryCN5 papers
8 papers · 1 filter
Classification based deep learning models for lung cancer and disease using medical images
Ahmad Chaddad, Jihao Peng, Yihang Wu
The use of deep learning (DL) in medical image analysis has significantly improved the ability to predict lung cancer. In this study, we introduce a novel deep convolutional neural…
Gland Segmentation Via Dual Encoders and Boundary-Enhanced Attention
Huadeng Wang, Jiejiang Yu, Bingbing Li +4
Accurate and automated gland segmentation on pathological images can assist pathologists in diagnosing the malignancy of colorectal adenocarcinoma. However, due to various gland sh…
DIAS: A Dataset and Benchmark for Intracranial Artery Segmentation in DSA sequences
Wentao Liu, Tong Tian, Lemeng Wang +11
The automated segmentation of Intracranial Arteries (IA) in Digital Subtraction Angiography (DSA) plays a crucial role in the quantification of vascular morphology, significantly c…
Super-resolution Reconstruction of Single Image for Latent features
Xin Wang, Jing-Ke Yan, Jing-Ye Cai +3
Single-image super-resolution (SISR) typically focuses on restoring various degraded low-resolution (LR) images to a single high-resolution (HR) image. However, during SISR tasks,…
Can autism be diagnosed with AI?
Ahmad Chaddad, Jiali li, Qizong Lu +5
Radiomics with deep learning models have become popular in computer-aided diagnosis and have outperformed human experts on many clinical tasks. Specifically, radiomic models based…
Deep Radiomic Analysis for Predicting Coronavirus Disease 2019 in Computerized Tomography and X-ray Images
Ahmad Chaddad, Lama Hassan, Christian Desrosiers
This paper proposes to encode the distribution of features learned from a convolutional neural network using a Gaussian Mixture Model. These parametric features, called GMM-CNN, ar…