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Mobile laser scanning can be used to efficiently measure tree stems with high precision. However, the laser beam divergence will affect the accuracy if a curved surface, such as a tree stem, is to be measured. In this work we present a method for correction of the bias introduced by the physical properties of the emitted laser pulses. The aim of the work was to estimate tree stem centres and stem diameters for different heights above the ground level (i.e., stem vector). We used two different laser scanners (Ouster OS0; Ouster OS1) mounted on a forest harvester operating in northern Sweden (64.3° N, long. 19.8° E). The beam divergences were 0.35 and 0.18 degrees, respectively. For validation, the trees were measured with stationary laser scanning (Leica RTC360). The mobile laser scanning data were combined with data from an inertial navigation system (INS) and point clouds were derived using a simultaneously localization and mapping (SLAM) algorithm. To avoid influence of errors remaining after the SLAM computations, laser data were in a first step processed scan-wise to estimate circle centre and circle radius based on laser returns from the tree stems. The correction of the stem diameter bias caused by beam divergence was in this step also performed using a new algorithm using solely data from the same scan rotation. In addition, laser returns from the ground were extracted for each scan rotation. In a second step, circle estimated and ground returns from all scans were merged for further processing. The circle locations were in this step clustered to build up tree stems, and a ground elevation model was created using an active contour surface to normalize height values. Stem diameter profiles (stem vectors) were estimated for each tree stem using all circles associated to an individual tree. A priori information about tree stem allometry was used for the final interpolation of stem diameter vectors. The vectors of stem diameters and tree stem centre locations were validated using data from the stationary laser scanning. The results show that stem diameter estimation bias could be corrected using the new scan-wise bias correction method. Furthermore, stem shape could be estimated with sufficiently high accuracy to make the method useful for practical applications. The method could therefore be used in the future for real-time bucking optimization to improve utilization efficiency of wood resources.