PhotIQA: A photoacoustic image data set with image quality ratings
Image quality assessment (IQA) is crucial in the evaluation stage of novel algorithms operating on images, including traditional and machine learning based methods. Due to the lack of available quality-rated medical images, most commonly used full-reference IQA measures have been developed and tested for natural images. Reported pitfalls and inconsistencies arising when applying such measures for medical images are not surprising, as they rely on different properties than natural images. In photoacoustic imaging (PAI), especially, standard benchmarking approaches for assessing the quality of image reconstructions are lacking. PAI is a multi-physics imaging modality, in which two inverse problems have to be solved, which makes the application of IQA measures uniquely challenging due to both, acoustic and optical, artifacts. To support the development and testing of IQA measures we assembled PhotIQA, a data set consisting of 1134 photoacoustic images. The images were rated by five experts across five quality properties in a full-reference setting, where the detailed rating enables usage beyond PAI. The data set with the images and corresponding ratings is publicly available on Zenodo.
Code (0)
등록된 구현이 없습니다.
Tasks
Image Quality AssessmentSimilar Papers 제목 키워드 기반
Limited-View Photoacoustic Imaging Reconstruction Via High-quality Self-supervised Neural Representation
In practical applications within the human body, it is often challenging to fully encompass the target tissue or organ, necessitating the use of limited-view arrays, which can lead to the loss of crucial information. Add…
Image ReconstructionFully Dense UNet for 2D Sparse Photoacoustic Tomography Artifact Removal
Photoacoustic imaging is an emerging imaging modality that is based upon the photoacoustic effect. In photoacoustic tomography (PAT), the induced acoustic pressure waves are measured by an array of detectors and used to …
Model based learning for accelerated, limited-view 3D photoacoustic tomography
Recent advances in deep learning for tomographic reconstructions have shown great potential to create accurate and high quality images with a considerable speed-up. In this work we present a deep neural network that is s…
Tomographic ReconstructionsLimited View and Sparse Photoacoustic Tomography for Neuroimaging with Deep Learning
Photoacoustic tomography (PAT) is a nonionizing imaging modality capable of acquiring high contrast and resolution images of optical absorption at depths greater than traditional optical imaging techniques. Practical con…
Image ReconstructionModel-Based Photoacoustic Image Reconstruction using Compressed Sensing and Smoothed L0 Norm
Photoacoustic imaging (PAI) is a novel medical imaging modality that uses the advantages of the spatial resolution of ultrasound imaging and the high contrast of pure optical imaging. Analytical algorithms are usually em…
compressed sensingImage Reconstruction