Methods and apparatus for HILN characterization using convolutional neural network

A characterization method, comprising:

• capturing multiple images of a specimen container including a serum or plasma portion of a specimen;
• inputting image data from the multiple images to a convolutional neural network and processing the image data with the convolutional neural network;
• and
• outputting from the convolutional neural network a classification of the serum or plasma portion as being one or more of hemolytic, icteric, lipemic, and normal;
• wherein the convolutional neural network comprises an architecture including a deconvolution layer.

A characterization method, comprising:

• capturing multiple images of a specimen container including a serum or plasma portion of a specimen;
• inputting image data from the multiple images to a convolutional neural network and processing the image data with the convolutional neural network;
• and
• outputting from the convolutional neural network a classification of the serum or plasma portion as being one or more of hemolytic, icteric, lipemic, and normal;
• wherein the convolutional neural network comprises an architecture including a SoftMax layer.

A characterization method, comprising:

• capturing multiple images of a specimen container including a serum or plasma portion of a specimen;
• inputting image data from the multiple images to a convolutional neural network and processing the image data with the convolutional neural network;
• and
• outputting from the convolutional neural network a classification of the serum or plasma portion as being one or more of hemolytic, icteric, lipemic, and normal;
• wherein the classification of the serum or plasma portion comprises outputting a fine-grained index for one or more of hemolysis, icterus, and lipemia.

A characterization method, comprising:

• capturing multiple images of a specimen container including a serum or plasma portion of a specimen;
• inputting image data from the multiple images to a convolutional neural network and processing the image data with the convolutional neural network;
• and
• outputting from the convolutional neural network a classification of the serum or plasma portion as being one or more of hemolytic, icteric, lipemic, and normal;
• wherein the convolutional neural network comprises:
• a first network branch including N′-class segmentation outputs, and
• a second network branch including N-class output options classes for each of hemolytic, icteric, and lipemic.

A quality check module for pre-screening a specimen for presence of an interferent, comprising:

• an image capture device configured to capture multiple images of a specimen container containing a serum or plasma portion of a specimen;
• and
• a computer coupled to the image capture device, the computer configured and capable of being operated to:
• input image data from the multiple images to a convolutional neural network and process the image data with the convolutional neural network, the convolutional neural network comprising an architecture that includes a deconvolution layer, and
• output from the convolutional neural network a classification of the serum or plasma portion as being one or more of hemolytic, icteric, lipemic, and normal.

A specimen testing apparatus, comprising:

• a track;
• a carrier moveable on the track and configured to contain a specimen container containing a serum or plasma portion of a specimen;
• image capture devices arranged around the track and configured to capture multiple images of a specimen container and the serum or plasma portion of the specimen from multiple viewpoints;
• and
• a computer coupled to the image capture devices, the computer configured and capable of being operated to:
• input image data from the multiple images to a convolutional neural network and process the image data with the convolutional neural network, the convolutional neural network comprising an architecture that includes a SoftMax layer, and
• output from the convolutional neural network a classification of the serum or plasma portion as being one or more of hemolytic, icteric, lipemic, and normal.