A computer-implemented method of training a machine-learning algorithm to perform histopathological image analysis, the method comprising: obtaining, by the computer, a plurality of first microscopic images of first histological specimens that have been stained with a first marker; obtaining, by the computer, a respective plurality of second microscopic images of second histological specimens that have been stained with a second marker, different from the first marker, each one of the second histological specimens corresponding to a respective one of the first histological specimens; obtaining, by the computer, a respective plurality of mask images generated for the second microscopic images, each mask image identifying a histological feature of interest highlighted in the respective second microscopic image by the second marker; for each first microscopic image and the respective second microscopic image and mask image: obtaining (230, 270), by the computer, a transformation that maps between the first microscopic image and the second microscopic image, and aligning (232, 272), by the computer, the first microscopic image and the mask image, using the transformation; and training, by the computer, the machine-learning algorithm with the plurality of aligned first microscopic images and mask images, thereby training the machine-learning algorithm to predict, from another first microscopic image of another histological specimen stained with the first marker, a histological feature of interest that would be highlighted in that specimen by the second marker. obtaining, by the computer, a plurality of first microscopic images of first histological specimens that have been stained with a first marker; obtaining, by the computer, a respective plurality of second microscopic images of second histological specimens that have been stained with a second marker, different from the first marker, each one of the second histological specimens corresponding to a respective one of the first histological specimens; obtaining, by the computer, a respective plurality of mask images generated for the second microscopic images, each mask image identifying a histological feature of interest highlighted in the respective second microscopic image by the second marker; for each first microscopic image and the respective second microscopic image and mask image: obtaining (230, 270), by the computer, a transformation that maps between the first microscopic image and the second microscopic image, and aligning (232, 272), by the computer, the first microscopic image and the mask image, using the transformation; and obtaining (230, 270), by the computer, a transformation that maps between the first microscopic image and the second microscopic image, and aligning (232, 272), by the computer, the first microscopic image and the mask image, using the transformation; and training, by the computer, the machine-learning algorithm with the plurality of aligned first microscopic images and mask images, thereby training the machine-learning algorithm to predict, from another first microscopic image of another histological specimen stained with the first marker, a histological feature of interest that would be highlighted in that specimen by the second marker.