A computer-implemented method for performing block retrieval on a block to be processed of a urine sediment image, comprising: using a decision tree to perform block retrieval on the block to be processed, wherein the decision tree comprises a judgment node and a leaf node, and the judgment node judges the block to be processed to make it reach the leaf node by using a block retrieval feature in a block retrieval feature set to form a block retrieval result at the leaf node, wherein the block retrieval result comprises a retrieved block; and integrating the block retrieval results of the decision tree so as to form a final block retrieval result; characterized by using a plurality of decision trees to perform block retrieval on the block to be processed, wherein at least two decision trees in the plurality of decision trees are different in structures thereof and/or judgments performed by the judgment nodes thereof by using the block retrieval feature and the step of using a plurality of decision trees to perform block retrieval on the block to be processed comprises: on each decision tree, in response to the block to be processed being judged by the judgment node and reaching the leaf node, acquiring a block belonging to the leaf node as a block retrieval result, wherein only an index of a block belonging to a leaf node of a decision tree is stored in the leaf node, and the block is stored in a database and wherein the block belonging to the leaf node is set in a manner as follows: training the plurality of decision trees by using a training sample block in a training sample block set so that on each decision tree, the training sample block is judged by the judgment node and reaches a corresponding leaf node, and becomes a block belonging to the corresponding leaf node. using a decision tree to perform block retrieval on the block to be processed, wherein the decision tree comprises a judgment node and a leaf node, and the judgment node judges the block to be processed to make it reach the leaf node by using a block retrieval feature in a block retrieval feature set to form a block retrieval result at the leaf node, wherein the block retrieval result comprises a retrieved block; and integrating the block retrieval results of the decision tree so as to form a final block retrieval result; characterized by using a plurality of decision trees to perform block retrieval on the block to be processed, wherein at least two decision trees in the plurality of decision trees are different in structures thereof and/or judgments performed by the judgment nodes thereof by using the block retrieval feature and the step of using a plurality of decision trees to perform block retrieval on the block to be processed comprises: on each decision tree, in response to the block to be processed being judged by the judgment node and reaching the leaf node, acquiring a block belonging to the leaf node as a block retrieval result, wherein only an index of a block belonging to a leaf node of a decision tree is stored in the leaf node, and the block is stored in a database and wherein the block belonging to the leaf node is set in a manner as follows: training the plurality of decision trees by using a training sample block in a training sample block set so that on each decision tree, the training sample block is judged by the judgment node and reaches a corresponding leaf node, and becomes a block belonging to the corresponding leaf node.