Quantitative Absorption Tomography Achieves 3D Volumetric Imaging from Brightfield Microscopy

Researchers have long sought methods to move beyond the limitations of traditional brightfield microscopy, which primarily delivers two-dimensional qualitative images. Now, Yoonjae Chung, Sehyun Lee and Herve Hugonnet, from the KAIST Institute for Health Science and Technology, alongside Chulmin Oh, Weisun Park and Yeon Wook Kim et al., present quantitative absorption tomography (QAT), a novel technique that reconstructs high-resolution, three-dimensional volumetric absorption data from standard brightfield images. This breakthrough enables quantitative and spectrally resolved 3D imaging without the need for complex equipment like interferometers or sample rotation, offering a significant advance in fields ranging from cell biology to histopathology. By successfully demonstrating QAT’s capabilities in diverse samples , including living cells, plant tissue and crucially, millimeter-scale human tissue sections , the team paves the way for practical, label-free 3D histopathological analysis and a deeper understanding of biological structure.

Quantitative 3D Absorption Imaging via Tomography offers high-resolution

Scientists have unveiled quantitative absorption tomography (QAT), a groundbreaking computational approach reconstructing high-resolution volumetric absorption coefficient distributions from brightfield focal stacks. This innovative technique overcomes the inherent limitations of conventional brightfield microscopy, which is typically restricted to two-dimensional qualitative imaging and struggles to systematically investigate three-dimensional volumetric architecture. The research establishes a method for quantitative, spectrally resolved 3D absorption imaging without the need for interferometry, sample rotation, or specialized hardware, representing a significant leap forward in optical microscopy. The team achieved this breakthrough by modelling absorption image formation in logarithmic intensity space and applying deconvolution with an absorption transfer function, a physics-based inverse model, to yield quantitative volumetric absorption maps.
This formulation allows for the direct measurement of optical absorption, the physical origin of contrast in brightfield histology, rather than relying on indirect inference or qualitative attenuation signals. Validating QAT involved the use of spectrally selective phantoms, confirming accurate 3D localization and wavelength-specific absorption reconstruction, and demonstrating its ability to provide absorption-specific contrast complementary to refractive index tomography. Experiments show that QAT successfully visualizes absorption-specific contrast in living melanocytes and intact plant tissue, offering long-term, label-free monitoring of melanogenesis and resolving endogenous pigment distributions in optically complex samples. Furthermore, the study extends the technique’s capabilities to millimeter-scale volumes of H&E-stained human tissue, revealing 3D histological microarchitecture without the laborious process of serial sectioning.

This achievement unlocks the potential for practical 3D histopathology, offering a non-destructive and efficient method for analysing tissue samples. This work opens new avenues for 3D biology, histopathology, and spatial analysis of stained and pigmented specimens using familiar imaging workflows. By bridging the gap between conventional brightfield imaging and volumetric optical imaging, QAT offers a practical pathway towards comprehensive three-dimensional tissue analysis, potentially revolutionizing disease diagnosis and clinical decision-making across a broad range of conditions. The. Experiments revealed that QAT accurately models absorption image formation in logarithmic intensity space and applies deconvolution with an absorption transfer function to achieve these results.

Results demonstrate that QAT successfully validates against spectrally selective phantoms, confirming its ability to reconstruct absorption coefficients with high fidelity. The research measured the complex refractive index of a sample, defined as n(x, y, z) = n(x, y, z) + iκ(x, y, z), where ‘n’ describes refraction and ‘κ’ represents absorption. Under weakly scattering conditions, a linear relationship between measured image intensity attenuation, S = log[I(r) / I0(r)], and the object’s complex refractive index was derived: S = HAVimag + HPVreal, where Vimag and Vreal are the imaginary and real parts of the scattering potential. Tests prove that QAT scales to millimeter-scale volumes of H&E-stained human tissue, revealing 3D histological microarchitecture without the need for serial sectioning.

The team illuminated samples with structured patterns, achieving well-conditioned forward operators for joint reconstruction of κ and n within the intended resolution range. Measurements confirm that the separation of the extinction coefficient (κ) and refractive index (n) is formulated as a linear inverse problem, utilising intensity stacks acquired under distinct illumination conditions. The breakthrough delivers quantitative, 3D absorption imaging using brightfield microscopy, bridging a critical gap between conventional brightfield imaging and volumetric optical imaging. Researchers implemented a programmable brightfield microscopy system and employed spectrally selective absorption phantoms, consisting of cyan, magenta, and yellow laser printer toner particles, to validate the technique. Following deconvolution, QAT reconstructed three-dimensional absorption volumes with strong suppression of out-of-focus background and accurate spatial localisation of the CMY particles, demonstrating submicron resolution across millimeter-scale volumes. This approach offers a practical pathway toward 3D biology, histopathology, and spatial analysis of stained and pigmented specimens using familiar imaging workflows.

Quantitative Absorption Tomography visualises living samples in 3D

Scientists have developed quantitative absorption tomography (QAT), a new computational imaging framework reconstructing three-dimensional absorption contrast from brightfield intensity image stacks. This technique quantitatively maps absorption coefficient distributions, enabling high-resolution volumetric imaging without the need for interferometry, sample rotation, or specialised hardware. QAT models absorption image formation in logarithmic.