In this work we propose the use of a content-adaptive mesh model (CAMM) for tomographic image reconstruction. In the proposed framework, the image to be reconstructed is first modeled by an efficient mesh representation. The image is then obtained through estimation of the nodal values from the measured data. The use of a CAMM can greatly alleviate the ill-posed nature of the reconstruction problem, thereby leading to improved quality in the reconstructed images. In addition, it can also lead to development of efficient numerical reconstruction algorithms. The proposed methods are tested using gated cardiac-perfusion images. Results demonstrate that the proposed approach achieves the best performance when compared to several commonly used methods for image reconstruction, and produces results very rapidly.

For more information refer to: 
Tomographic Image Reconstruction Using Content-Adaptive Mesh Modeling
IEEE ICIP October 7-10, 2001 Thessaloniki, Greece

From left to right in top row: Original phantom, Filtered backprojection reconstruction, ML-EM reconstruction. Bottom row: MAP reconstruction, MESH-LS (least square) reconstruction, and MESH-EM reconstruction. 

For more details send a request to: jovan [at] brankov [dot] com