
    In a medical imaging system analyzing bilateral tissue scans, develop a function that identifies the unique pixel intensity value representing a potential anomaly from a sorted sequence of intensity measurements, where normal tissue patterns appear in pairs. The system receives a sorted array of pixel intensity values, where all values except one appear exactly twice, and must efficiently locate this singular intensity value that could indicate an asymmetric tissue formation or potential tumor.
    

    
def search(arr):
    """
    In a medical imaging system analyzing bilateral tissue scans, develop a function that identifies the unique pixel intensity value representing a potential anomaly from a sorted sequence of intensity measurements, where normal tissue patterns appear in pairs. The system receives a sorted array of pixel intensity values, where all values except one appear exactly twice, and must efficiently locate this singular intensity value that could indicate an asymmetric tissue formation or potential tumor.
    

    """
def search(arr):
    """
    In a medical imaging system analyzing bilateral tissue scans, develop a function that identifies the unique pixel intensity value representing a potential anomaly from a sorted sequence of intensity measurements, where normal tissue patterns appear in pairs. The system receives a sorted array of pixel intensity values, where all values except one appear exactly twice, and must efficiently locate this singular intensity value that could indicate an asymmetric tissue formation or potential tumor.
    

    """
    n = len(arr)
    XOR = 0
    for i in range(n):
        XOR = XOR ^ arr[i]
    return XOR