A method of characterizing a specimen container, comprising: processing pixel data of an image of a specimen container (102, 102C, 102D) containing a specimen (212, 212C, 212D) therein to determine whether the specimen container includes a serum portion or a plasma portion using a classification network executing on a computer; and characterized by transforming pixel data of an image determined by the classification network to include a serum portion into transformed-pixel data that matches pixel data of a previously-collected image of a plasma portion having an appearance that corresponds to an appearance of the serum portion without affecting any HILN (hemolytic, icteric, lipemic, and normal) characteristics present in the pixel data of the image using a transformation network executing on the computer, wherein the transforming comprises modifying pixel color, contrast, intensity, or brightness data of the image determined by the classification network to include the serum portion, and wherein the method further comprises: processing the transformed-pixel data to determine an HILN category of the serum portion using a segmentation/classification/regression network executing on the computer; processing pixel data of an image determined by the classification network to include a plasma portion to determine an HILN category of the plasma portion using the segmentation/classification/regression network executing on the computer; and outputting from the segmentation/classification/regression network a determined HILN category (540H, 540I, 540L, 540N) for each image having pixel data processed by the segmentation/classification/regression network using an interface module coupled to the computer, wherein the segmentation/classification/regression network has been trained with only images of plasma samples, and wherein the outputting further comprises outputting from the segmentation/classification/regression network a classification index category comprising hemolytic, icteric, lipemic, and normal classes and sub-classes using the interface module coupled to the computer. processing pixel data of an image of a specimen container (102, 102C, 102D) containing a specimen (212, 212C, 212D) therein to determine whether the specimen container includes a serum portion or a plasma portion using a classification network executing on a computer; and characterized by transforming pixel data of an image determined by the classification network to include a serum portion into transformed-pixel data that matches pixel data of a previously-collected image of a plasma portion having an appearance that corresponds to an appearance of the serum portion without affecting any HILN (hemolytic, icteric, lipemic, and normal) characteristics present in the pixel data of the image using a transformation network executing on the computer, wherein the transforming comprises modifying pixel color, contrast, intensity, or brightness data of the image determined by the classification network to include the serum portion, and wherein the method further comprises: processing the transformed-pixel data to determine an HILN category of the serum portion using a segmentation/classification/regression network executing on the computer; processing pixel data of an image determined by the classification network to include a plasma portion to determine an HILN category of the plasma portion using the segmentation/classification/regression network executing on the computer; and outputting from the segmentation/classification/regression network a determined HILN category (540H, 540I, 540L, 540N) for each image having pixel data processed by the segmentation/classification/regression network using an interface module coupled to the computer, wherein the segmentation/classification/regression network has been trained with only images of plasma samples, and wherein the outputting further comprises outputting from the segmentation/classification/regression network a classification index category comprising hemolytic, icteric, lipemic, and normal classes and sub-classes using the interface module coupled to the computer. processing the transformed-pixel data to determine an HILN category of the serum portion using a segmentation/classification/regression network executing on the computer; processing pixel data of an image determined by the classification network to include a plasma portion to determine an HILN category of the plasma portion using the segmentation/classification/regression network executing on the computer; and outputting from the segmentation/classification/regression network a determined HILN category (540H, 540I, 540L, 540N) for each image having pixel data processed by the segmentation/classification/regression network using an interface module coupled to the computer, wherein the segmentation/classification/regression network has been trained with only images of plasma samples, and wherein the outputting further comprises outputting from the segmentation/classification/regression network a classification index category comprising hemolytic, icteric, lipemic, and normal classes and sub-classes using the interface module coupled to the computer.