A computer-implemented method of reconstructing MRI images, the method comprising: - for each coil of a receiver coil array of an MRI apparatus, determining a respective set of two or more coil sensitivity maps (431, 432) using an autocalibration protocol such as an ESPIRiT autocalibration protocol densely sampling a part of the k-space and determining a respective coil sensitivity data structure comprising the respective two or more coil sensitivity maps (431, 432) in a stitched arrangement along a given direction in the k-space, a stitching factor of the stitched arrangement corresponding to the count of the two or more coil sensitivity maps (431, 442) of the respective set, - for each coil of the receiver coil array, acquiring k-space data using an undersampling trajectory in the k-space and determining a respective measurement data structure comprising the respective k-space data rearranged in the k-space on an adjusted k-space trajectory that is determined by stretching the k-space trajectory by the stitching factor along the given direction, and - based on the coil sensitivity data structures determined for the coils of the receiver coil array and further based on the measurement data structures determined for the coils of the receiver coil array, performing an iterative optimization based on a SENSE reconstruction algorithm to obtain at least one MRI image, wherein the iterative optimization comprises, for at least some iterations of multiple iterations of the iterative optimization, a regularization operation and a data-consistency operation, wherein the data-consistency operation is based on differences between the measurement data structures and respective synthesized measurement data structures, the synthesized MRI measurement data structures being based on a k-space representation of at least one prior MRI image of the multiple iterations and the adjusted undersampling trajectory and the coil sensitivity data structures. - for each coil of a receiver coil array of an MRI apparatus, determining a respective set of two or more coil sensitivity maps (431, 432) using an autocalibration protocol such as an ESPIRiT autocalibration protocol densely sampling a part of the k-space and determining a respective coil sensitivity data structure comprising the respective two or more coil sensitivity maps (431, 432) in a stitched arrangement along a given direction in the k-space, a stitching factor of the stitched arrangement corresponding to the count of the two or more coil sensitivity maps (431, 442) of the respective set, - for each coil of the receiver coil array, acquiring k-space data using an undersampling trajectory in the k-space and determining a respective measurement data structure comprising the respective k-space data rearranged in the k-space on an adjusted k-space trajectory that is determined by stretching the k-space trajectory by the stitching factor along the given direction, and - based on the coil sensitivity data structures determined for the coils of the receiver coil array and further based on the measurement data structures determined for the coils of the receiver coil array, performing an iterative optimization based on a SENSE reconstruction algorithm to obtain at least one MRI image, wherein the iterative optimization comprises, for at least some iterations of multiple iterations of the iterative optimization, a regularization operation and a data-consistency operation, wherein the data-consistency operation is based on differences between the measurement data structures and respective synthesized measurement data structures, the synthesized MRI measurement data structures being based on a k-space representation of at least one prior MRI image of the multiple iterations and the adjusted undersampling trajectory and the coil sensitivity data structures. wherein the iterative optimization comprises, for at least some iterations of multiple iterations of the iterative optimization, a regularization operation and a data-consistency operation, wherein the data-consistency operation is based on differences between the measurement data structures and respective synthesized measurement data structures, the synthesized MRI measurement data structures being based on a k-space representation of at least one prior MRI image of the multiple iterations and the adjusted undersampling trajectory and the coil sensitivity data structures.