NCA-GENM Exam Dumps | You are designing a IJ-Net architecture for semantic segmentation of medical images. Your input images

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Question 179/192

You are designing a IJ-Net architecture for semantic segmentation of medical images. Your input images are 512x512 with 3 channels.
You want to ensure the final output segmentation map is also 512x512. Which of the following design choices are crucial for achieving this resolution, considering the downsampling and upsampling stages?

A. Using only strided convolutions for downsampling and transposed convolutions for upsampling without skip connections.

B. Ensuring that the number of downsampling and upsampling blocks are equal, and employing skip connections from corresponding encoder layers to decoder layers.

C. Using max pooling with a kernel size of 3x3 and stride of 2 for downsampling, and nearest neighbor interpolation for upsampling.

D. Employing only IXI convolutions in the bottleneck of the U-Net architecture to reduce computational complexity.

E. Using a batch size of 1 during training to simplify memory management.

Correct Answer: B

Maintaining the same resolution in IJ-Net requires symmetric downsampling and upsampling and the crucial use of skip connections. These connections pass feature maps from the downsampling (encoder) path to the corresponding layers in the upsampling (decoder) path, allowing the decoder to recover spatial information lost during downsampling. Option A omits skip connections. Option C's nearest neighbor interpolation can lead to blocky artifacts. Option D describes a bottleneck optimization unrelated to output resolution. Option E is about training parameters.

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