Abstract: Systems and methods for image segmentation in accordance with embodiments of the invention are illustrated. One embodiment includes a method for segmenting medical images, including obtaining a medical image of a patient, the medical image originating from a medical imaging device, providing the medical image of the patient to a fully convolutional neural network (FCN), where the FCN comprises a loss layer, and where the loss layer utilizes the CE-IOU loss function, segmenting the medical image such that at least one region of the medical image is classified as a particular biological structure, and providing the medical image via a display device.

Abstract: Systems and methods for performing image processing in accordance with embodiments of the invention are illustrated. One embodiment includes an imaging system including at least one processor, an input/output interface in communication with a medical imaging device, a display in communication with the processor, and a memory in communication with the processor, including image data obtained from a medical imaging device, where the image data describes at least one image describing at least one region of a patient's body, and an image processing application, where the image processing application directs the processor to preprocess the image data, identify pathological features within the preprocessed image data, calculate the likelihood that the at least one region described by the at least one image is afflicted by a disease, and provide a disease classification substantially instantaneously describing the disease and the likelihood of the disease being present in the region via the display.