1091. Acute Stroke (30)
One important factor to identify acute stroke (急性脑卒中) is the volume of the stroke core. Given the results of image analysis in which the core regions are identified in each MRI slice, your job is to calculate the volume of the stroke core.
Input Specification:
Each input file contains one test case. For each case, the first line contains 4 positive integers: M, N, L and T, where M and N are the sizes of each slice (i.e. pixels of a slice are in an M by N matrix, and the maximum resolution is 1286 by 128); L (<=60) is the number of slices of a brain; and T is the integer threshold (i.e. if the volume of a connected core is less than T, then that core must not be counted).
Then L slices are given. Each slice is represented by an M by N matrix of 0's and 1's, where 1 represents a pixel of stroke, and 0 means normal. Since the thickness of a slice is a constant, we only have to count the number of 1's to obtain the volume. However, there might be several separated core regions in a brain, and only those with their volumes no less than T are counted. Two pixels are "connected" and hence belong to the same region if they share a common side, as shown by Figure 1 where all the 6 red pixels are connected to the blue one.

Figure 1
Output Specification:
For each case, output in a line the total volume of the stroke core.
Sample Input:3 4 5 2 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 0 0 1 1 0 0 1 1 1 0 1 1 0 1 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0Sample Output:
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注意这是一个三维的立体模型,所以有前后上下左右六个方向进行遍历,用dfs可能会栈溢出,所以用bfs
code:
#include <iostream>
#include <cstdio>
#include <cstring>
#include <queue>
using namespace std;
int m,n,L,t;
int G[62][1288][130];
int vis[62][1288][130];
int dir[6][3] = {{1,0,0},{-1,0,0},{0,1,0},{0,-1,0},{0,0,1},{0,0,-1}};
int sum,num;
struct node{
int x,y,z;
}s,nexts;
void bfs(int x,int y,int z){
if(vis[z][x][y] || !G[z][x][y]) return;
queue<node>q;
s.x = x;
s.y = y;
s.z = z;
vis[z][x][y] = 1;
q.push(s);
while(!q.empty()){
s = q.front();
num++;
q.pop();
for(int i = 0; i < 6; i++){
int xx,yy,zz;
nexts.x = xx = s.x + dir[i][0];
nexts.y = yy = s.y + dir[i][1];
nexts.z = zz = s.z + dir[i][2];
if(xx >= 0 && xx < m && yy >= 0 && y < n && zz >= 0 && zz < L && G[zz][xx][yy] && !vis[zz][xx][yy]){
vis[zz][xx][yy] = 1;
q.push(nexts);
}
}
}
}
int main(){
int i,j,k;
memset(vis,0,sizeof(vis));
cin >> m >> n >> L >> t;
for(k = 0; k < L; k++){
for(i = 0; i < m; i++){
for(j = 0; j < n; j++){
cin >> G[k][i][j];
}
}
}
sum = 0;
for(k = 0; k < L; k++){
for(i = 0; i < m; i++){
for(j = 0; j < n; j++){
num = 0;
bfs(i,j,k);
if(num >= t) sum += num;
}
}
}
printf("%d\n",sum);
return 0;
}

本文介绍了一种计算急性脑卒中核心体积的方法。通过分析MRI切片图像,使用三维遍历算法(如BFS)来确定卒中区域,并统计有效体积。适用于识别和评估急性脑卒中患者的病情。
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