Systems and methods for image segmentation

A system for training a region of interest (ROI) segmentation model corresponding to a target image resolution, comprising:

• at least one storage device storing a set of instructions;
• and
• at least one processor configured to communicate with the at least one storage device, wherein when executing the set of instructions, the at least one processor is configured to direct the system to perform operations including:
• obtaining a preliminary model including a plurality of convolutional layers;
• and
• generating the ROI segmentation model corresponding to the target image resolution by training the preliminary model, wherein
• the plurality of convolutional layers include at least a first convolutional layer and a second convolutional layer downstream to the first convolutional layer, and
• a count of input channels of the first convolutional layer is greater than a count of output channels of the first convolutional layer.

A system for image segmentation, comprising:

• at least one storage device including a set of instructions;
• and
• at least one processor configured to communicate with the at least one storage device, wherein when executing the set of instructions, the at least one processor is configured to direct the system to perform operations including:
• obtaining a target image including a region of interest (ROI);
• segmenting, from the target image, a preliminary region representative of the ROI using a ROI segmentation model;
• and
• segmenting, from the preliminary region, a target region representative of the ROI, wherein
• the ROI segmentation model includes a plurality of convolutional layers, the plurality of convolutional layers at least including a first convolutional layer and a second convolutional layer downstream to the first convolutional layer, a count of input channels of the first convolutional layer is greater than a count of output channels of the first convolutional layer.