Results 91 to 100 of about 896 (171)

CAP-IQA: Context-Aware Prompt-Guided CT Image Quality Assessment

CoRR
Prompt-based methods, which encode medical priors through descriptive text, have been only minimally explored for CT Image Quality Assessment (IQA). While such prompts can embed prior knowledge about diagnostic quality, they often introduce bias by reflecting idealized definitions that may not hold under real-world degradations such as noise, motion ...
Kazi Ramisa Rifa, Jie Zhang, Abdullah Al Zubaer Imran   +2 more
openaire   +2 more sources

Charting the path forward: CT image quality assessment - an in-depth review

Journal of King Saud University: Computer and Information Sciences
Computed Tomography (CT) is a frequently utilized imaging technology that is employed in the clinical diagnosis of many disorders. However, clinical diagnosis, data storage, and management are faced with significant challenges posed by a huge volume of ...
Siyi Xun, Qiaoyu Li, Xiaohong Liu, Pu Huang, Guangtao Zhai, Yue Sun, Peter H. N. de With, Mingxiang Wu, Tao Tan   +8 more
doaj   +1 more source

SA-IQA: Redefining Image Quality Assessment for Spatial Aesthetics with Multi-Dimensional Rewards

CoRR
In recent years, Image Quality Assessment (IQA) for AI-generated images (AIGI) has advanced rapidly; however, existing methods primarily target portraits and artistic images, lacking a systematic evaluation of interior scenes. We introduce Spatial Aesthetics, a paradigm that assesses the aesthetic quality of interior images along four dimensions ...
Yuan Gao, Jin Song
openaire   +2 more sources

PrISM-IQA: Image Quality Assessment Made Practical for Smartphone Photography

Existing smartphone image quality assessment (IQA) methods commonly reduce perceptual quality to a single score. However, this scalar formulation is poorly aligned with practical image signal processor (ISP) tuning, where engineers must identify specific quality issues, estimate their severities, and determine whether they are acceptable or require ...
Zhai, Shuyan, He, Jiaqi, Zhang, Weixia, Wang, Liang, Lee, Zhenjie, Zhang, Zufeng, Ma, Kede   +6 more
openaire   +2 more sources

IQAGPT: computed tomography image quality assessment with vision-language and ChatGPT models

Visual Computing for Industry, Biomedicine, and Art
Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various tasks and attracted increasing interest as a natural language interface across many domains. Recently, large vision-language models (VLMs) that learn rich
Zhihao Chen, Bin Hu, Chuang Niu, Tao Chen, Yuxin Li, Hongming Shan, Ge Wang   +6 more
doaj   +1 more source

Grounding-IQA: Grounding Multimodal Language Model for Image Quality Assessment

Accepted to ICLR 2026.
Chen, Zheng, Zhang, Xun, Li, Wenbo, Pei, Renjing, Song, Fenglong, Min, Xiongkuo, Liu, Xiaohong, Yuan, Xin, Guo, Yong, Zhang, Yulun   +9 more
openaire   +2 more sources

Enhancing Pest Detection in Deep Learning Through a Systematic Image Quality Assessment and Preprocessing Framework

Journal of Experimental and Theoretical Analyses
This study addresses the critical challenge of variable image quality in deep learning-based automated pest identification. We propose a holistic pipeline that integrates systematic Image Quality Assessment (IQA) with tailored preprocessing to enhance ...
Shuyi Jia, Maryam Horri Rezaei, Barmak Honarvar Shakibaei Asli   +2 more
doaj   +1 more source

MS-IQA: A Multi-scale Feature Fusion Network for PET/CT Image Quality Assessment

Accepted to MICCAI ...
Siqiao Li, Chen Hui, Wei Zhang 0192, Rui Liang, Chenyue Song, Feng Jiang 0001, Haiqi Zhu, Zhixuan Li, Hong Huang, Xiang Li   +9 more
openaire   +2 more sources

Perceptual no-reference image quality assessment with meta-learning by graph representation learning and multi-scale feature fusion. [PDF]

PLoS One
Jia Y, Wei L.
europepmc   +1 more source

From discarding to leveraging: quality-aware collaborative learning for robust diabetic retinopathy grading. [PDF]

Front Med (Lausanne)
Pan Y, Cai X, Xiong P, Mei F, Wang Z, Hong J.   +5 more
europepmc   +1 more source