CN103631568A - Medical-image-oriented multi-thread parallel computing method - Google Patents
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Abstract
The invention discloses a medical-image-oriented multi-thread parallel computing method, and relates to a medical image processing method, in particular to an image processing and optimizing method for applying a multi-thread thought and a programming method to medical images. On a processor supporting hyper threading or a multi-core technology, multi-thread programming is performed by using hardware resources on the processor by means of software. The method comprises the following steps: partitioning a medical image needing to be processed into image blocks which can be processed independently and grouping the image blocks; simultaneously running a plurality of threads in different kernels of different processors at the same moment by using a multi-thread technology; enabling each thread to execute image block groups with relatively average workload from an original image respectively and to carry out parallel processing on an original image processing task set till all threads finish processing; and summarizing processing results, and outputting. Through the overall multi-thread parallel computation, the execution efficiency of image processing can be increased, and the aim of accelerating computation is fulfilled.
Description
Technical field
The present invention relates to medical image processing method, especially relate to a kind of multithreads computing method towards medical image.
Background technology
Medical image (comprising magnetic resonance image (MRI), computed tomography images and ultrasonoscopy etc.) is processed important role in medical image science and clinical practice.Along with development and the growing interest of people to medical treatment & health of image processing techniques, wish that reduce the working time of Medical Image Processing.The appearance of hyperthread and multi-core technology, provides possibility for accelerating Medical Image Processing.
The universal microprocessor 4004 in first, the whole world that 1971 Nian， Intel release, consists of 2300 transistors.Gordon mole just proposed by industry, to be regarded as afterwards " Moore's Law " of creed---every mistake 18 months at that time, and transistor size that can be integrated on chip will double.Because transistor size integrated on chip piece is more, mean that arithmetic speed is that dominant frequency is just faster.Yet, 2005, when approaching 4 gigahertz (GHZ) Shi， Intel and United States advanced microelectronic component company, dominant frequency finds, speed also can run into the oneself limit: that is exactly simple dominant frequency lifting, obvious Hoisting System overall performance.Just Hyper-Threading and polycaryon processor technology had in succession been there is afterwards.In February, 2002, Intel company has adopted first Hyper-Threading in the trendy Xeon of 130nm that the code name of its release is Prestonia.Hyper-Threading utilizes special hardware instruction, two logic kernels are modeled to two phy chips, allow single processor core can use Thread-Level Parallelism to calculate, and then the standby time of minimizing central processing unit, improve the operational efficiency of central processing unit, the while is compatible multithreading operation system and software also.Meanwhile, International Business Machine Corporation (IBM) has issued first polycaryon processor in the world October calendar year 2001---and the double-core compacting instruction set processor of Power4 by name, it is integrated in the Power personal computer processor of two 64 on a chips.The polycaryon processor that has multimicroprocessor core for a processor, can be encapsulated in two or more independent processor cores integrated a plurality of chips in an integrated circuit (IC) chip or on a mainboard.Hyperthread and polycaryon processor technical development so far, have been widely used on ordinary individual's computer machine.Therefore, make full use of the computing machine that we can use, design multi-thread concurrent executive routine, raising computer program efficiency and resource utilization seem and are even more important.
Summary of the invention
The object of the present invention is to provide the multithreads computing method towards medical image based on hyperthread and polycaryon processor technology.
The present invention includes following steps:
1) source images is decomposed, be divided into can independent processing at least 2 little image blocks, reach and the processing of original image is divided into the subtask that a size is Q gathers;
2) use C language or open multiprocessing (Open Multi-Processing, OpenMP) Mutli-thread Programming Technology in language creates N thread, then Q the sub-set of tasks being obtained by step 1) decomposition all being given to N thread goes to carry out, each thread execution Q is divided by N subtask, when the aliquant N of Q, last thread may make an exception, and carries out Q to a N remainder subtask, wherein Q is general assignment number, the Thread Count that N is program creation;
3), if there is the operation that gathers to all image blocks in implementation, can use following two methods to carry out multithreading synchronous:
(1) use the multithreadings such as critical section to add lock technology, the source synchronous that realizes each thread gathers;
(2) preserve thread process result data in parent process, treat that all processes gather after finishing again.
In step 1), described source images is decomposed, the concrete grammar that is divided at least 2 little image blocks that can independent processing can be: first source images is carried out to border extension, source images after expansion be take to each pixel as starting point, source images is divided into little image block, reaches the processing of original image is divided into the subtask set that a size is Q.
In order to reduce the central processing unit resource consuming in thread creation, management and synchronizing process, when designing and writing multithread processing method, should avoid many batches of generations that create situation of source synchronous and thread as far as possible.
The present invention makes full use of hyperthread and many kernels of central processing unit in medical image (comprising magnetic resonance image (MRI), computed tomography images and ultrasonoscopy etc.) is processed, realize the parallel computation of Medical Image Processing thread level, the subtask with independence is assigned to concurrent execution in a plurality of threads, reduce the execution time of Medical Image Processing program, raising program operational efficiency, reaches the target of optimizing Medical Image Processing program.
Accompanying drawing explanation
Fig. 1 is the treatment scheme schematic diagram of serial task collection.
Fig. 2 is the treatment scheme schematic diagram of parallel task collection.
Fig. 3 is number of threads and the program execution time curve map of multithreads computing.In Fig. 3, first point of curve is processed the required time for serial program, the magnetic resonance image (MRI) that experiment condition is Windows7 operating system, 4 core processors, 8 hyperthreads, dominant frequency 3.4 GHzs, carry out based on non local image operator are processed, and its parameter situation is as table 3.
Embodiment
The embodiment of the present invention comprises the following steps:
1) source images is decomposed, be divided into can independent processing a plurality of little image block (example is as shown in table 1, first 64x64 image is carried out to border extension, image after expansion be take to each pixel as starting point, the little image block that source images is divided into 4096 8x8), reach the processing of original image has been divided into a subtask set that size is Q;
Table 1
In table 1, digital value represents pixel number, and the solid bold box region that adds is original image, in fine and closely woven dotted line frame be to take the image block 1 that pixel 1 is pivot expansion, adds thick dashed line frame region and be to take the image block that pixel 2 expands as pivot.
2) use C language or open multiprocessing (Open Multi-Processing, OpenMP) Mutli-thread Programming Technology in language creates N thread, then Q the subtask being obtained by decomposition in step 1 divided equally to N thread and gone to carry out, divided by N subtask, (wherein Q is general assignment number to each thread execution Q, N is the Thread Count of program creation) individual, when the aliquant N of Q, last thread may make an exception, and carries out Q to a N remainder subtask;
3), if there is the operation that gathers to all image blocks in implementation, can use following two methods to carry out multithreading synchronous:
(1) use the multithreadings such as critical section to add lock technology, the source synchronous that realizes each thread gathers;
(2) preserve thread process result data in parent process, treat that all processes gather after finishing again.
In order to reduce the central processing unit resource consuming in thread creation, management and synchronizing process, when designing and writing multithread processing method, should avoid many batches of generations that create situation of source synchronous and thread as far as possible.
Below provide concrete implementation step:
1) source images piecemeal: by source images according to certain rule resolve into can independent processing a plurality of little image block, the processing of original image has been divided into a task-set that size is Q;
Piecemeal situation in the embodiment of the present invention is as follows: as table 1, be 64 * 64 former figure images of need processing, totally 4096 pixels.Piecemeal in the present embodiment is determined the image block of little 8 * 8 by each pixel, mark is carried out to image block in the position (top left corner pixel of image block or other pixel) of the interior determined pixel by image block, and the follow-up processing to this image block is called as a subtask.Wherein, table 2 is the parameter declaration of image block program.
Table 2
2) multi-thread concurrent Processing tasks.
Utilize the Mutli-thread Programming Technology of C language, application programming interface (the Application Programming Interface that comprises Windows or Linux, API) function library or open multiprocessing (Open Multi-Processing, OpenMP) programming language, create N thread, then Q task in the task-set obtaining will be decomposed in step 1), all give N each Q of thread divided by N subtask, last thread may make an exception, and carries out Q to a N remainder subtask.
Fig. 1 provides the treatment scheme schematic diagram of serial task collection, Fig. 2 provides the treatment scheme schematic diagram of parallel task collection, for the image that has the task-set of 64 * 64 number of sub images pieces is processed (processing time of remembering the image block that each task needs is 1 chronomere), if adopt traditional serial program processing mode, all images that are disposed, will consume 64 * 64 unit interval.The multithreads computing method that adopts this patent to propose, supposes to carry out Processing tasks with 16 threads, and each thread parallel is carried out 16 * 16 tasks and can be reduced to 4 * 64 unit interval the whole processing time so.The resource consumption of removing operating system establishment and management thread, multithread programs still has acceleration capacity at double.
Because the establishment of thread, management, destruction etc. all can consume the resource of central processing unit, should not repeatedly create thread carries out task distribution, and best in processing procedure (but being not limited to) only carried out establishment and the disposable task of a multithreading and distributed.When the number of threads creating and processor core calculation (comprising hyperthread virtual core) are quite or when bigger, executive routine can maximized use cpu resource, thereby reaches maximized acceleration object.As can be seen from Figure 3, in the calculating of 4 core 8 hyperthreads, process based on non local image operator (Xiaobo Qu, Yingkun Hou, Fan Lam, Di Guo, Jianhui Zhong, Zhong Chen.Magnetic resonance image reconstruction from undersampled measurements using a patch-based nonlocal operator, Medical Image Analysis, DOI:10.1016/j.media.2013.09.007, 2013) magnetic resonance image (MRI) Processing Example, can be reduced to 0.4s from 1.6s computing time, multi-threaded parallel will shorten to original 1/4 computing time.Wherein, table 3 is parameter service condition in embodiment.
The non local image operator parameter declaration of table 3
3) carry out if desired multithreading synchronous.
In implementation, if any gathering operation, can use the multithreadings such as critical section to add lock technology and realize source synchronous, gather; In addition, if internal memory is abundant and permission, temporary result data, in parent process storehouse, are treated by main thread unification, to be gathered after all process technology.
Claims (2)
1. towards the multithreads computing method of medical image, it is characterized in that comprising the following steps:
1) source images is decomposed, be divided into can independent processing at least 2 little image blocks, reach and the processing of original image is divided into the subtask that a size is Q gathers;
2) use C language or open multiprocessing (Open Multi-Processing, OpenMP) Mutli-thread Programming Technology in language creates N thread, then Q the sub-set of tasks being obtained by step 1) decomposition all being given to N thread goes to carry out, each thread execution Q is divided by N subtask, when the aliquant N of Q, last thread may make an exception, and carries out Q to a N remainder subtask, wherein Q is general assignment number, the Thread Count that N is program creation;
3), if there is the operation that gathers to all image blocks in implementation, use following two methods to carry out multithreading synchronous:
(1) use the multithreadings such as critical section to add lock technology, the source synchronous that realizes each thread gathers;
(2) preserve thread process result data in parent process, treat that all processes gather after finishing again.
2. as claimed in claim 1 towards the multithreads computing method of medical image, it is characterized in that in step 1), described source images is decomposed, the concrete grammar that is divided at least 2 little image blocks that can independent processing is: first source images is carried out to border extension, source images after expansion be take to each pixel as starting point, source images is divided into little image block, reaches the processing of original image is divided into the subtask set that a size is Q.
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