Fluorescence molecular tomography (FMT) is a depth-resolved macroscopic optical imaging technique, and it can locate and quantify the fluorescent molecular probes inside biological tissue; it has a great potential in studying the protein interaction, analyzing the mechanism of drug action, and evaluating the therapeutic effect of tumor. However, one of the key challenges in FMT is that the inverse problem is highly ill-conditioned, which means that image reconstruction is sensitive to the measurement noise and the numerical errors. To improve results of image reconstruction, we should improve the performance of the imaging system as much as possible to reduce measurement noise, improve the accuracy of the forward problem of FMT to reduce the numerical error, and meanwhile alleviate and overcome the ill-condition of the inverse problem to strengthen the anti-noise ability. We introduce the research progress of FMT in image reconstruction on the last two aspects.