The inventive concepts herein relate to performing block retrieval on a block to be processed of a urine sediment image. The method comprises: using a plurality of decision trees to perform block retrieval on the block to be processed, wherein each of the plurality of decision trees 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, and 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 integrating the block retrieval results of the plurality of decision trees so as to form a final block retrieval result.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for performing block retrieval on a block to be processed of a urine sediment image, comprising: using a plurality of decision trees to perform block retrieval on the block to be processed, wherein each of the plurality of decision trees 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 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 integrating the block retrieval results of the plurality of decision trees so as to form a final block retrieval result. 2. The method according to claim 1, characterized in that the step of integrating the block retrieval results of the plurality of decision trees comprises: voting for the blocks retrieved by the plurality of decision trees, wherein if there are m decision trees in the plurality of decision trees altogether which retrieve a specific block, the ballot of the specific block is m, with m being a positive integer; and arranging the blocks retrieved by the plurality of decision trees in a descending order of the ballot. 3. The method according to claim 2, characterized in that only the retrieved blocks with ballots greater than a preset threshold value are listed. 4. The method according to claim 1, characterized in that 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 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. 5. The method according to claim 4, characterized in that a classification tag is preset for the training sample block in the training sample block set so that the retrieved blocks comprised in the block retrieval result also carry classification tags. 6. An apparatus for performing block retrieval on a block to be processed of a urine sediment image, comprising: a block retrieval unit configured to use a plurality of decision trees to perform block retrieval on the block to be processed, wherein each of the plurality of decision trees 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 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 an integration unit configured to integrate the block retrieval results of the plurality of decision trees so as to form a final block retrieval result. 7. The apparatus according to claim 6, characterized in that the integration unit is further configured to: vote for the blocks retrieved by the plurality of decision trees, wherein if there are m decision trees in the plurality of decision trees altogether which retrieve a specific block, the ballot of the specific block is m, with m being a positive integer; and arrange the blocks retrieved by the plurality of decision trees in a descending order of the ballot. 8. The apparatus according to claim 7, characterized in that the integration unit is further configured to only list the retrieved blocks with ballots greater than a preset threshold value. 9. The apparatus according to claim 6, characterized in that the block retrieval unit is configured to, on each decision tree, in response to the block to be processed being judged by the judgment node and reaching the leaf node, acquire a block belonging to the leaf node as a block retrieval result, 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. 10. The apparatus according to claim 9, characterized in that a classification tag is preset for the training sample block in the training sample block set so that the retrieved blocks comprised in the block retrieval result also carry classification tags. 11. A device for performing block retrieval on a block to be processed of a urine sediment image, comprising: a memory for storing executable instructions, the executable instructions, when executed, implementing the method of claim 1; and a processor for executing the executable instructions. 12. A machine-readable medium on which an executable instruction is stored, wherein when the executable instruction is executed, a machine is caused to perform the method of claim 1.