Electron paramagnetic resonance imaging (EPRI) is a technique that has been used for in vivo oxygen imaging of small animals. In continuous wave (CW) EPRI, the measurement can be interpreted as a sampled 4D Radon transform of the image function. The conventional filtered-backprojection (FBP) algorithm has been used widely for reconstructing images from full knowledge of the Radon transform acquired in CW EPRI. In practical applications of CW EPRI, one often is interested in information only in a region of interest (ROI) within the imaged subject. It is desirable to accurately reconstruct an ROI image only from partial knowledge of the Radon transform because acquisition of the partial data set can lead to considerable reduction of imaging time. The conventional FBP algorithm cannot, however, reconstruct accurate ROI images from partial knowledge of the Radon transform of even dimension. In this work, we describe two new algorithms, which are referred to as the backprojection filtration (BPF) and minimum-data filtered-backprojection (MDFBP) algorithms, for accurate ROI-image reconstruction from a partial Radon transform (or, truncated Radon transform) in CW EPRI. We have also performed numerical studies in the context of ROI-image reconstruction of a synthetic 2D image with density similar to that found in a small animal EPRI. This demonstrates both the inadequacy of the conventional FBP algorithm and the success of BPF and MDFBP algorithms in ROI reconstruction. The proposed ROI imaging approach promises a means to substantially reduce image acquisition time in CW EPRI.