aot-biomaps
Acousto-Optic Tomography Reconstruction Library
Decision gist · record as of 2026-08-14
Yes, if you are working on acousto-optic tomography research or biomedical imaging reconstruction. The library is actively maintained, has low install friction, offers both CPU and GPU paths, and implements multiple state-of-the-art algorithms. However, verify the license status before use in proprietary work, and confirm that k-wave-python is available if acoustic simulation is required. Not relevant for general-purpose image processing or non-AOT applications.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.8.
- GPU support (cupy-cuda12x) requires CUDA 12.x; CPU-only mode available via AOT_BIOMAPS_CPU_ONLY=true environment variable or --cpu flag.
- Low install friction; pure Python wheel with straightforward pip installation.
License · maintenance · safety
(unclear) — License treatment is unclear—the description mentions MIT but the fact sheet contains no SPDX identifier or confirmed license metadata. Verify the actual license before use in proprietary or restricted contexts.
last release 2026-07-29 (16 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 124,301 downloads/mo, #11,876 on PyPI
Alternatives
Verify before relying
pip install aot-biomaps
import numpy as np
from AOT_biomaps import Tomography, AlgebraicRecon
from AOT_biomaps.AOT_Recon.ReconEnums import ReconType
experiment = Tomography(
optic_image_path="path/to/optic_image.npy",
acoustic_fields_path="path/to/acoustic_fields.npy"
)
recon = AlgebraicRecon(
experiment=experiment,
reconType=ReconType.Algebraic,
optimizerType="MLEM",
numIterations=100
)
recon.run(withTumor=True)- Whether MIT license in description is the actual license or if license metadata will be clarified in PyPI
- Whether k-wave-python is truly optional or required for acoustic simulation features
- Actual performance benchmarks (21.5x GPU speedup claimed) on typical user hardware
- Whether sparse matrix implementations (CSR, SELL-C-sigma) are production-ready or experimental
What it is and what it does
AOT_biomaps is a specialized library for Acousto-Optic Tomography, a biomedical imaging modality that combines acoustic and optical physics. It implements multiple tomographic reconstruction algorithms (MLEM, PDHG, LS, DEPIERRO, MAPEM, LBFGS) with both CPU (NumPy) and GPU (CuPy) backends, allowing automatic fallback between implementations. The library also provides acoustic wave simulation, optical media modeling, signal processing utilities, and 2D/3D visualization.
The package is designed for research in biomedical imaging and combines advanced reconstruction mathematics with practical optimization for sparse matrix operations. It depends on numpy, scipy, tqdm, matplotlib, and optionally cupy-cuda12x for GPU acceleration and k-wave-python for acoustic simulation. Installation is straightforward via pip, with a CPU-only mode available for systems without CUDA.
Use it for
- Reconstruct 3D biomedical images from acousto-optic tomography sensor data using iterative algorithms like MLEM or PDHG.
- Simulate acoustic wave propagation and optical interactions in heterogeneous tissue models for AOT experiment design.
- Accelerate tomographic reconstruction on GPU hardware to reduce computation time from minutes to seconds.
- Process and visualize 2D/3D tomographic datasets with built-in filtering, backprojection, and Radon transform tools.
- Benchmark different sparse matrix formats (CSR, SELL-C-sigma) for memory efficiency in large-scale reconstruction problems.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are working on acousto-optic tomography research or biomedical imaging reconstruction.
The library is actively maintained, has low install friction, offers both CPU and GPU paths, and implements multiple state-of-the-art algorithms. However, verify the license status before use in proprietary work, and confirm that k-wave-python is available if acoustic simulation is required. Not relevant for general-purpose image processing or non-AOT applications.
Install
aot-biomaps on PyPI
Before you install
Low install friction; pure Python wheel with straightforward pip installation. Active maintenance (latest release 16 days ago). Six runtime dependencies including numpy, scipy, and optional GPU support via cupy-cuda12x; CPU-only installation available via environment variable.
Requires Python >=3.8. GPU support (cupy-cuda12x) requires CUDA 12.x; CPU-only mode available via AOT_BIOMAPS_CPU_ONLY=true environment variable or --cpu flag.
License in practice
License treatment is unclear—the description mentions MIT but the fact sheet contains no SPDX identifier or confirmed license metadata. Verify the actual license before use in proprietary or restricted contexts.
Quickstart
pip install aot-biomaps
import numpy as np
from AOT_biomaps import Tomography, AlgebraicRecon
from AOT_biomaps.AOT_Recon.ReconEnums import ReconType
experiment = Tomography(
optic_image_path="path/to/optic_image.npy",
acoustic_fields_path="path/to/acoustic_fields.npy"
)
recon = AlgebraicRecon(
experiment=experiment,
reconType=ReconType.Algebraic,
optimizerType="MLEM",
numIterations=100
)
recon.run(withTumor=True)Verify before relying
- Whether MIT license in description is the actual license or if license metadata will be clarified in PyPI
- Whether k-wave-python is truly optional or required for acoustic simulation features
- Actual performance benchmarks (21.5x GPU speedup claimed) on typical user hardware
- Whether sparse matrix implementations (CSR, SELL-C-sigma) are production-ready or experimental
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagesnumpyscipytqdmmatplotlibcupy-cuda12xk-wave-python |
| Maintenance | Actively maintained 16 days since the last release |
| First released | |
| Downloads | 124,301 / month, #11,876 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: aot_biomaps-2.9.905-py3-none-any.whl
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