🚀🚀🚀 We're thrilled to announce that our paper has been accepted for publication in Medical Image Analysis!
This project presents a PyQt implementation for Super-Resolution Photoacoustic Angiography Assisted by Images Forged from Hand-Drawn Graffiti. Leveraging the concept of Image Super-Resolution via Iterative Refinement Project, our application allows users to draw graffiti on a board, generating its corresponding photoacoustic version within minutes. The implementation is coded using PyQt5.
# First, download the model from Google Drive and place it in ./experiments
# [Google Drive Model](https://drive.google.com/file/d/1XWXWG4DAw0ZPd0N_3r-7jQMF5WMKyOG0/view?usp=share_link)
cd dir_of_the_project
python ./main.py
(a)-(g): The schematic illustrates the training process for super-resolution blood vessel images in Photoacoustic Angiography (PAA) forged from hand-drawn doodles. It includes steps such as generating rain-like noise, hand-drawn doodles, input image generation, normalized Gaussian noise, PAA image generation, normalized PAA image, and reconstructed super-resolution PAA image. (a')-(f'): The corresponding schematic for training super-resolution blood vessel images in PAA forged from cropped images.
Note: PyQt5-based hand-drawn graffiti for photoacoustic images generation. The GUI with graffiti and without graffiti is displayed below.
Note: We generate different kinds of photoacoustic images by adding noise of Gaussian distribution. The left two are input images, while the right two are their corresponding photoacoustic versions.
The left two are input images while the right are their photoacoustic version.
Note: The shallow and deep feature extraction of SwinIR enables us to utilize the self-similarity of blood vessel images. These results also prove the abilities of our proposed method in forging photoacoustic images.
(a) High-resolution ground truth; (b) Reconstructed by Bicubic algorithm; (c)-(f) Reconstructed by SwinIR trained with various datasets. (c) COCO dataset; (d) mouse brain PAA images; (e) real human lips PAA images; (f) forged human lips PAA images.
** Photoacoustic, Microscopy, Diffusion Model, Biomedical Imaging, Medical Imaging