Binary Classification on clinical breast ultrasound dataset benchmark leaderboard · SOTA2 Research

Binary Classification on clinical breast ultrasound dataset

97.67AccuracyRad-VLSM

Evaluation Results

Method	Links
Rad-VLSM2026.05		97.67	—	97.62	—	97.65	97.69
AHF-UNet (CLSCA)2026.05		96.63	—	81.91	—	88.87	97.13
CA-Net2026.05		96.54	—	78.67	—	86.94	97.16
AHF-UNet (UAFF)2026.05		96.49	—	82.01	—	88.68	96.53
SwinUnet2026.05		96.43	—	81.71	—	88.52	96.58
U-Net2026.05		96.34	—	73.86	—	82.58	93.63
U-Net++2026.05		96.07	—	76.21	—	84.53	94.9
Unext2026.05		95.92	—	80.95	—	88.49	97.58
U-Net-iAFF2026.05		95.88	—	83.4	—	88.65	94.62
U-NetAFF2026.05		95.85	—	79.29	—	86.49	95.13
Bruno et al.2026.05		95.2	—	92.4	—	94.4	96.6
DCSAU2026.05		94.88	—	75.1	—	83.27	93.45
Rad-VLSM2026.05		94.07	97.55	98.41	89.09	94.66	—
TransUnet2026.05		93.46	—	75.87	—	83.49	92.86
Multi-task Transformers2026.05		89.8	—	65.4	—	77.3	94.4
CUNet2026.05		89.72	—	72.52	—	81.67	93.57
MIAFEx2026.05		82.3	87.82	82.24	82.24	82.29	—
SegNet2026.05		82.13	—	69.44	—	78.87	91.26
Mask R-CNN2026.05		80.9	—	74.4	—	75.4	76.8
ADSR-net2026.05		79.46	87.93	77.78	81.03	78.5	—
DiffMIC2026.05		76.79	86.59	68.52	84.48	74	—
MambaMIC2026.05		75.9	82.27	85	67.44	75.76	—
Densenet2026.05		75.9	80.17	83.72	67.5	75.71	—
MedMamba2026.05		74.7	76.28	74.4	75	74.7	—
ViT2026.05		73.49	72.13	51.16	97.5	73.78	—
ResNet502026.05		71.08	79.59	65.12	77.5	71.01	—
UniFormer-Small2026.05		68.67	71.45	72.09	65	68.63	—
PVT-Small2026.05		59.04	59.53	81.4	35	56.63	—
ConvNext-Tiny2026.05		57.83	58.49	60.47	55	57.81	—
Vim-Tiny2026.05		57.83	63.43	86.05	27.5	53.77	—